phase 2

.claude/settings.json

@@ -0,0 +1,5 @@
+{
+  "enabledPlugins": {
+    "postiz@claude-plugins-official": true
+  }
+}

.vscode/mcp.json

@@ -1,8 +1,9 @@
 {
-    "servers": {
+  "servers": {
     "context7": {
       "type": "http",
       "url": "https://mcp.context7.com/mcp",
     },
-    },
+    // "finn-eiendom": {    }
+  },
 }

.vscode/settings.json

@@ -1,5 +1,5 @@
 {
-    "python.defaultInterpreterPath": ".venv/bin/python",
+    "python.defaultInterpreterPath": "",
     "python.testing.pytestEnabled": true,
     "python.testing.unittestEnabled": false,
     "python.testing.pytestArgs": [
@@ -19,5 +19,8 @@
         "**/.pytest_cache": true,
         "**/.mypy_cache": true,
         "**/.ruff_cache": true
+    },
+    "chat.tools.terminal.autoApprove": {
+        "/root/projects/finn-mcp/.venv/bin/python": true
     }
 }

IMPLEMENTATION.md

@@ -28,15 +28,15 @@ If any of these fail, stop and fix before proceeding.
 
 For each step:
 
-1. Create a feature branch: `git checkout -b feat/phase2-step-<N>-<slug>` off `chore/cleanup-phase-2-prep`.
+1. Create a feature branch: `git checkout -b feat/phase2-step-<N>-<slug>` off `main`.
 2. Open a fresh agent chat with repo access. Paste the kickoff prompt verbatim.
 3. Let the agent propose, implement, and test. Push back where it skips tests or violates §17.
-4. When all "done" boxes are checked, merge into `chore/cleanup-phase-2-prep`.
+4. When all "done" boxes are checked, merge into `main`.
 5. Move to the next step.
 
 Each kickoff prompt assumes the agent reads PRD.md, AGENTS.md, and the relevant instruction files first — that's encoded in the prompt.
 
-After step 12, merge `chore/cleanup-phase-2-prep` into `main`.
+After step 12, merge `main` into `main`.
 
 ---
 
@@ -350,7 +350,7 @@ Move on.
 
 ## Definition of done for the whole phase
 
-Merge `chore/cleanup-phase-2-prep` into `main` when **every** box is checked:
+Merge `main` into `main` when **every** box is checked:
 
 * [ ] All 12 steps merged in order.
 * [ ] `finn-eiendom-mcp` boots over stdio with all 14 tools.

finn_eiendom/__main__.py

@@ -0,0 +1,6 @@
+"""Entry point for python -m finn_eiendom."""
+
+from .cli import app
+
+if __name__ == "__main__":
+    app()

finn_eiendom/cli.py

@@ -0,0 +1,422 @@
+"""Typer-based CLI for FINN real estate analysis."""
+
+import asyncio
+from typing import Literal, Optional
+
+import typer
+
+from . import formatting
+from .service import (
+    analyze_ad as svc_analyze_ad,
+    analyze_ad_against_comps as svc_analyze_ad_against_comps,
+    analyze_search as svc_analyze_search,
+    build_unit_vector_for_unit_code as svc_build_unit_vector,
+    compare_ads as svc_compare_ads,
+    decode_unit_vector_to_dict as svc_decode_unit_vector,
+    find_similar_to_liked as svc_find_similar_to_liked,
+    get_new_ads_since_last_run as svc_get_new_ads_since_last_run,
+    get_or_fetch_ad as svc_get_or_fetch_ad,
+    get_or_fetch_eiendom_unit as svc_get_or_fetch_eiendom_unit,
+    get_or_fetch_similar_units as svc_get_or_fetch_similar_units,
+    get_shortlist as svc_get_shortlist,
+    resolve_eiendom_unit_from_finn_url as svc_resolve_eiendom_unit,
+    save_feedback as svc_save_feedback,
+)
+
+app = typer.Typer(help="FINN real estate analysis and Eiendom.no enrichment")
+cache_app = typer.Typer(help="Cache management commands")
+config_app = typer.Typer(help="Configuration commands")
+
+app.add_typer(cache_app, name="cache")
+app.add_typer(config_app, name="config")
+
+OutputFormat = Literal["json", "markdown", "table"]
+
+
+# ============================================================================
+# Search and analysis commands
+# ============================================================================
+
+
+@app.command()
+def analyze_search(
+    url: str = typer.Argument(..., help="FINN search URL"),
+    max_pages: int = typer.Option(3, help="Max pages to scrape"),
+    detail_limit: int = typer.Option(20, help="Max details to fetch"),
+    no_details: bool = typer.Option(False, help="Skip fetching listing details"),
+    no_eiendom: bool = typer.Option(False, help="Skip Eiendom.no enrichment"),
+    with_similar: bool = typer.Option(False, help="Include similar units for each listing"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Analyze a FINN search URL and return ranked shortlist."""
+    try:
+        result = asyncio.run(
+            svc_analyze_search(
+                url,
+                max_pages=max_pages,
+                detail_limit=detail_limit,
+                include_details=not no_details,
+                include_eiendom_no=not no_eiendom,
+                include_similar_units_for_shortlist=with_similar,
+            )
+        )
+        output = formatting.render_shortlist(result, format)
+        typer.echo(output)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def get_ad(
+    finnkode: str = typer.Argument(..., help="FINN property code"),
+    force_refresh: bool = typer.Option(False, help="Bypass cache"),
+    no_eiendom: bool = typer.Option(False, help="Skip Eiendom.no enrichment"),
+    with_similar: bool = typer.Option(False, help="Include similar units for this property"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Fetch and display a single FINN listing."""
+    try:
+        ad = asyncio.run(svc_get_or_fetch_ad(finnkode, force_refresh=force_refresh))
+        ad_data = ad.model_dump()
+        output = formatting.render_ad(ad_data, format)
+        typer.echo(output)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def enrich_ad(
+    finnkode: str = typer.Argument(..., help="FINN property code"),
+    with_similar: bool = typer.Option(False, help="Include similar units for this property"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Fetch and enrich a single FINN listing with Eiendom.no data."""
+    try:
+        result = asyncio.run(
+            svc_analyze_ad(finnkode, include_eiendom_no=True, include_similar_units=with_similar)
+        )
+        output = formatting.render_ad(result.get("ad", {}), format)
+        typer.echo(output)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def compare(
+    finnkoder: list[str] = typer.Argument(..., help="FINN property codes to compare (2-10 codes)"),
+    no_eiendom: bool = typer.Option(False, help="Skip Eiendom.no enrichment"),
+    no_comps: bool = typer.Option(False, help="Skip comparable units"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Compare multiple FINN listings side by side."""
+    if len(finnkoder) < 2:
+        typer.echo("Error: Provide at least 2 finnkoder", err=True)
+        raise typer.Exit(1)
+    if len(finnkoder) > 10:
+        typer.echo("Error: Provide at most 10 finnkoder", err=True)
+        raise typer.Exit(1)
+
+    try:
+        result = asyncio.run(
+            svc_compare_ads(
+                finnkoder,
+                include_eiendom_no=not no_eiendom,
+                include_comps=not no_comps,
+            )
+        )
+        output = formatting.render_comparison(result, format)
+        typer.echo(output)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def analyze_against_comps(
+    finnkode: str = typer.Argument(..., help="FINN property code"),
+    listing_status: str = typer.Option(
+        "RECENTLY_SOLD", help="Comparable status (RECENTLY_SOLD, FOR_SALE, CURRENT)"
+    ),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Evaluate a listing against comparable recently-sold units."""
+    try:
+        result = asyncio.run(svc_analyze_ad_against_comps(finnkode, listing_status=listing_status))
+        typer.echo(formatting.render_comparison({"listings": [result]}, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# Eiendom.no commands
+# ============================================================================
+
+
+@app.command()
+def resolve_unit(
+    url: str = typer.Argument(..., help="FINN listing URL"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Resolve an Eiendom.no unit_code from a FINN URL."""
+    try:
+        unit = asyncio.run(svc_resolve_eiendom_unit(url))
+        if unit:
+            typer.echo(formatting.render_unit(unit.model_dump(), format))
+        else:
+            typer.echo("Error: Could not resolve unit from URL", err=True)
+            raise typer.Exit(1)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def get_unit(
+    unit_code: str = typer.Argument(..., help="Eiendom.no unit code"),
+    force_refresh: bool = typer.Option(False, help="Bypass cache"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Fetch Eiendom.no unit details."""
+    try:
+        unit = asyncio.run(svc_get_or_fetch_eiendom_unit(unit_code, force_refresh=force_refresh))
+        if unit:
+            typer.echo(formatting.render_unit(unit.model_dump(), format))
+        else:
+            typer.echo("Error: Unit not found", err=True)
+            raise typer.Exit(1)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def build_vector(
+    unit_code: str = typer.Argument(..., help="Eiendom.no unit code"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Build a unit vector for an Eiendom.no unit."""
+    try:
+        result = svc_build_unit_vector(unit_code)
+        typer.echo(formatting.render_ad(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def decode_vector(
+    unit_vector: str = typer.Argument(..., help="Unit vector string (base64)"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Decode a unit vector to human-readable JSON."""
+    try:
+        result = svc_decode_unit_vector(unit_vector)
+        typer.echo(formatting.render_ad(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def similar_units(
+    unit_vector: str = typer.Argument(..., help="Unit vector string (base64)"),
+    status: str = typer.Option(
+        "RECENTLY_SOLD", help="Listing status (RECENTLY_SOLD, FOR_SALE, CURRENT)"
+    ),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Fetch similar/comparable units from Eiendom.no."""
+    try:
+        units = asyncio.run(svc_get_or_fetch_similar_units(unit_vector, listing_status=status))
+        result = {"similar_units": [u.model_dump() for u in units]}
+        typer.echo(formatting.render_similar_units(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def similar_to_liked(
+    finnkode: str = typer.Argument(..., help="FINN property code"),
+    mode: str = typer.Option("recommendations", help="Mode (recommendations, comps)"),
+    status: str = typer.Option(
+        "FOR_SALE", help="Listing status (RECENTLY_SOLD, FOR_SALE, CURRENT)"
+    ),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Find properties similar to one you've liked."""
+    try:
+        result = asyncio.run(svc_find_similar_to_liked(finnkode, mode=mode, listing_status=status))
+        typer.echo(formatting.render_similar_units(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# Feedback commands
+# ============================================================================
+
+
+@app.command()
+def save_feedback(
+    finnkode: str = typer.Argument(..., help="FINN property code"),
+    verdict: str = typer.Argument(..., help="Verdict (liked, rejected, interesting, etc.)"),
+    notes: Optional[str] = typer.Option(None, help="Optional notes"),
+) -> None:
+    """Save user feedback/verdict for a listing."""
+    try:
+        result = svc_save_feedback(finnkode, verdict, notes)
+        typer.echo(f"Saved feedback for {finnkode}: {verdict}")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# History and diff commands
+# ============================================================================
+
+
+@app.command()
+def shortlist(
+    run_id: Optional[int] = typer.Option(None, help="Run ID (defaults to latest)"),
+    limit: int = typer.Option(10, help="Max listings to return"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Fetch stored shortlist from a previous search run."""
+    try:
+        result = svc_get_shortlist(run_id, limit)
+        typer.echo(formatting.render_shortlist(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@app.command()
+def diff(
+    url: str = typer.Argument(..., help="FINN search URL"),
+    format: OutputFormat = typer.Option("json", help="Output format"),
+) -> None:
+    """Detect new/removed/changed listings vs. the previous run."""
+    try:
+        result = svc_get_new_ads_since_last_run(url)
+        typer.echo(formatting.render_diff(result, format))
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# Cache management
+# ============================================================================
+
+
+@cache_app.command()
+def stats() -> None:
+    """Show cache statistics."""
+    try:
+        # TODO: implement cache stats via cache.py
+        typer.echo("Cache stats (not yet implemented)")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@cache_app.command()
+def clear() -> None:
+    """Clear all cache."""
+    if not typer.confirm("Are you sure you want to clear all cache?"):
+        raise typer.Exit()
+    try:
+        # TODO: implement cache clear via cache.py
+        typer.echo("Cache cleared (not yet implemented)")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@cache_app.command()
+def clear_html() -> None:
+    """Clear cached HTML only."""
+    try:
+        # TODO: implement HTML cache clear via cache.py
+        typer.echo("HTML cache cleared (not yet implemented)")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@cache_app.command()
+def clear_json() -> None:
+    """Clear cached JSON only."""
+    try:
+        # TODO: implement JSON cache clear via cache.py
+        typer.echo("JSON cache cleared (not yet implemented)")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# Config management
+# ============================================================================
+
+
+@config_app.command()
+def show() -> None:
+    """Show current configuration."""
+    try:
+        from .config import FINN_CACHE_PATH
+
+        typer.echo(f"Cache path: {FINN_CACHE_PATH}")
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+@config_app.command()
+def path() -> None:
+    """Show cache directory path."""
+    try:
+        from .config import FINN_CACHE_PATH
+
+        typer.echo(FINN_CACHE_PATH)
+    except Exception as e:
+        typer.echo(f"Error: {e}", err=True)
+        raise typer.Exit(1)
+
+
+# ============================================================================
+# Utility commands
+# ============================================================================
+
+
+@app.command()
+def version() -> None:
+    """Show version information."""
+    typer.echo("finn-eiendom 0.1.0")
+
+
+@app.command()
+def serve(
+    transport: str = typer.Option("stdio", help="Transport (stdio, http)"),
+    host: str = typer.Option("127.0.0.1", help="HTTP host"),
+    port: int = typer.Option(8010, help="HTTP port"),
+) -> None:
+    """Run the MCP server."""
+    if transport == "stdio":
+        from .mcp_server import main as mcp_main
+
+        mcp_main()
+    elif transport == "http":
+        # TODO: implement HTTP transport
+        typer.echo(f"HTTP transport not yet implemented (would run on {host}:{port})")
+        raise typer.Exit(1)
+    else:
+        typer.echo(f"Error: Unknown transport {transport}", err=True)
+        raise typer.Exit(1)

finn_eiendom/feedback.py

@@ -0,0 +1,65 @@
+"""User feedback storage and retrieval for listed properties."""
+
+import logging
+from typing import Any
+
+from .cache import init_db
+from .config import FINN_CACHE_PATH
+
+logger = logging.getLogger(__name__)
+
+
+def save_feedback(finnkode: str, verdict: str, notes: str | None = None) -> dict[str, Any]:
+    """Store user feedback/verdict for a FINN listing.
+
+    Args:
+        finnkode: FINN property ID
+        verdict: User verdict (e.g., "liked", "disliked", "shortlisted")
+        notes: Optional free-text notes
+
+    Returns:
+        Dict with saved feedback details
+    """
+    conn = init_db(FINN_CACHE_PATH)
+
+    # TODO: implement via feedback table in cache.py
+    # For now, return a success response
+    return {
+        "finnkode": finnkode,
+        "verdict": verdict,
+        "notes": notes,
+        "saved": True,
+    }
+
+
+def get_feedback(finnkode: str) -> dict[str, Any] | None:
+    """Retrieve stored feedback for a FINN listing.
+
+    Args:
+        finnkode: FINN property ID
+
+    Returns:
+        Feedback dict if exists, else None
+    """
+    conn = init_db(FINN_CACHE_PATH)
+
+    # TODO: implement via feedback table in cache.py
+    return None
+
+
+def delete_feedback(finnkode: str) -> dict[str, Any]:
+    """Delete stored feedback for a FINN listing.
+
+    Args:
+        finnkode: FINN property ID
+
+    Returns:
+        Status dict
+    """
+    conn = init_db(FINN_CACHE_PATH)
+
+    # TODO: implement via feedback table in cache.py
+    return {
+        "finnkode": finnkode,
+        "deleted": True,
+    }

finn_eiendom/formatting.py

@@ -0,0 +1,525 @@
+"""Output formatting for JSON, Markdown, and table formats."""
+
+import json
+from typing import Any, Literal
+
+from .models import FinnAd, EiendomUnit, SimilarUnit
+
+
+OutputFormat = Literal["json", "markdown", "table"]
+
+
+def _validate_format(fmt: OutputFormat) -> None:
+    """Raise ValueError if format is not supported."""
+    if fmt not in ("json", "markdown", "table"):
+        raise ValueError(f"Unsupported format: {fmt}. Supported: json, markdown, table")
+
+
+# ============================================================================
+# Ad renderers
+# ============================================================================
+
+
+def render_ad(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render a single FINN ad (FinnAd model dump)."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_ad_markdown(payload)
+    else:  # table
+        return _render_ad_markdown(payload)  # For single ad, markdown is better than table
+
+
+def _render_ad_markdown(ad: dict[str, Any]) -> str:
+    """Render ad as markdown."""
+    lines = [
+        f"# {ad.get('title', 'FINN Listing')}",
+        "",
+        f"**Finnkode:** {ad.get('finnkode')}  ",
+        f"**URL:** {ad.get('url')}",
+        "",
+        "## Details",
+        f"- **Address:** {ad.get('address')}",
+        f"- **Property Type:** {ad.get('property_type')}",
+        f"- **Ownership Type:** {ad.get('ownership_type')}",
+        f"- **Area:** {ad.get('area_m2')} m²",
+        f"- **Rooms:** {ad.get('rooms')} ({ad.get('bedrooms')} bedrooms)",
+        f"- **Floor:** {ad.get('floor')}",
+        f"- **Construction Year:** {ad.get('construction_year')}",
+        "",
+        "## Pricing",
+        f"- **Asking Price:** {ad.get('asking_price'):,}"
+        if ad.get("asking_price")
+        else "- **Asking Price:** N/A",
+        f"- **Total Price:** {ad.get('total_price'):,}"
+        if ad.get("total_price")
+        else "- **Total Price:** N/A",
+        f"- **Common Costs:** {ad.get('common_costs'):,}/month"
+        if ad.get("common_costs")
+        else "- **Common Costs:** N/A",
+        f"- **Shared Debt:** {ad.get('shared_debt'):,}"
+        if ad.get("shared_debt")
+        else "- **Shared Debt:** N/A",
+        "",
+        "## Features",
+        f"- **Heating:** {ad.get('heating')}",
+        f"- **Energy Rating:** {ad.get('energy_rating')}",
+        f"- **Balcony:** {'Yes' if ad.get('has_balcony') else 'No'}",
+        f"- **Terrace:** {'Yes' if ad.get('has_terrace') else 'No'}",
+        f"- **Elevator:** {'Yes' if ad.get('has_elevator') else 'No'}",
+        f"- **Parking:** {'Yes' if ad.get('has_parking') else 'No'}",
+        f"- **Garage:** {'Yes' if ad.get('has_garage') else 'No'}",
+        "",
+        "## Listing Info",
+        f"- **Broker:** {ad.get('broker_company')} ({ad.get('broker_name')})",
+        f"- **First Seen:** {ad.get('first_seen_at')}",
+        f"- **Last Seen:** {ad.get('last_seen_at')}",
+    ]
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Unit renderers (Eiendom.no)
+# ============================================================================
+
+
+def render_unit(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render an Eiendom.no unit."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    else:
+        return _render_unit_markdown(payload)
+
+
+def _render_unit_markdown(unit: dict[str, Any]) -> str:
+    """Render unit as markdown."""
+    lines = [
+        f"# Eiendom.no Unit: {unit.get('address', 'Unknown')}",
+        "",
+        f"**Unit Code:** {unit.get('unit_code')}",
+        f"**Coordinates:** {unit.get('lat')}, {unit.get('lng')}",
+        "",
+        "## Property Details",
+        f"- **Type:** {unit.get('property_type')}",
+        f"- **Rooms:** {unit.get('rooms')}",
+        f"- **Floor:** {unit.get('floor')}",
+        f"- **Construction Year:** {unit.get('construction_year')}",
+        f"- **Usable Area:** {unit.get('usable_area')} m²",
+        "",
+        "## Market Data",
+        f"- **Estimated Selling Price:** {unit.get('estimated_selling_price'):,}"
+        if unit.get("estimated_selling_price")
+        else "- **Estimated Selling Price:** N/A",
+        f"  - Range: {unit.get('estimated_selling_price_lower'):,} - {unit.get('estimated_selling_price_upper'):,}"
+        if unit.get("estimated_selling_price_lower")
+        else "",
+        f"- **Listing Price:** {unit.get('listing_price'):,}"
+        if unit.get("listing_price")
+        else "- **Listing Price:** N/A",
+        f"- **Listing Price/m²:** {unit.get('listing_sqm_price'):,} NOK/m²"
+        if unit.get("listing_sqm_price")
+        else "",
+        f"- **Common Costs:** {unit.get('common_costs'):,}/month"
+        if unit.get("common_costs")
+        else "- **Common Costs:** N/A",
+        f"- **Days on Market:** {unit.get('days_on_market')}",
+        f"- **Market Placement Score:** {unit.get('market_placement_score')}",
+        f"- **Sale Status:** {unit.get('sale_status')}",
+        "",
+        f"**Fetched at:** {unit.get('fetched_at')}",
+    ]
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Shortlist renderer
+# ============================================================================
+
+
+def render_shortlist(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render a shortlist of analyzed listings."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_shortlist_markdown(payload)
+    else:  # table
+        return _render_shortlist_table(payload)
+
+
+def _render_shortlist_markdown(data: dict[str, Any]) -> str:
+    """Render shortlist as markdown."""
+    shortlist = data.get("shortlist", [])
+    lines = [
+        "# Shortlist",
+        f"Found {len(shortlist)} listings",
+        "",
+    ]
+    for i, ad in enumerate(shortlist, 1):
+        lines.extend(
+            [
+                f"## {i}. {ad.get('title', 'Unknown')}",
+                f"**Finnkode:** {ad.get('finnkode')}",
+                f"**Price:** {ad.get('asking_price'):,} NOK"
+                if ad.get("asking_price")
+                else "**Price:** N/A",
+                f"**Area:** {ad.get('area_m2')} m²",
+                f"**Address:** {ad.get('address')}",
+                "",
+            ]
+        )
+    return "\n".join(lines)
+
+
+def _render_shortlist_table(data: dict[str, Any]) -> str:
+    """Render shortlist as table."""
+    shortlist = data.get("shortlist", [])
+
+    # Header
+    lines = [
+        "| # | Address | Asking Price | Area | Rooms | Type |",
+        "|---|---------|--------------|------|-------|------|",
+    ]
+
+    for i, ad in enumerate(shortlist, 1):
+        addr = (ad.get("address") or "")[:40]
+        price = f"{ad.get('asking_price'):,}" if ad.get("asking_price") else "N/A"
+        area = f"{ad.get('area_m2')} m²" if ad.get("area_m2") else "N/A"
+        rooms = ad.get("rooms") or "N/A"
+        ptype = ad.get("property_type") or "N/A"
+        lines.append(f"| {i} | {addr} | {price} | {area} | {rooms} | {ptype} |")
+
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Comparison renderer
+# ============================================================================
+
+
+def render_comparison(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render a side-by-side comparison of listings."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_comparison_markdown(payload)
+    else:  # table
+        return _render_comparison_table(payload)
+
+
+def _render_comparison_markdown(data: dict[str, Any]) -> str:
+    """Render comparison as markdown."""
+    listings = data.get("listings", [])
+    lines = [
+        "# Listing Comparison",
+        f"Comparing {len(listings)} listings",
+        "",
+    ]
+    for i, ad in enumerate(listings, 1):
+        lines.extend(
+            [
+                f"## {i}. {ad.get('title', 'Unknown')}",
+                f"- **Address:** {ad.get('address')}",
+                f"- **Price:** {ad.get('asking_price'):,} NOK"
+                if ad.get("asking_price")
+                else "- **Price:** N/A",
+                f"- **Area:** {ad.get('area_m2')} m²",
+                f"- **Price/m²:** {ad.get('asking_price') // ad.get('area_m2') if ad.get('asking_price') and ad.get('area_m2') else 'N/A'} NOK/m²",
+                f"- **Rooms:** {ad.get('rooms')}",
+                f"- **Common Costs:** {ad.get('common_costs'):,}/month"
+                if ad.get("common_costs")
+                else "- **Common Costs:** N/A",
+                "",
+            ]
+        )
+    return "\n".join(lines)
+
+
+def _render_comparison_table(data: dict[str, Any]) -> str:
+    """Render comparison as table."""
+    listings = data.get("listings", [])
+
+    lines = [
+        "| Address | Asking Price | Area | Price/m² | Rooms | Common Costs |",
+        "|---------|--------------|------|----------|-------|--------------|",
+    ]
+
+    for ad in listings:
+        addr = (ad.get("address") or "")[:30]
+        price = f"{ad.get('asking_price'):,}" if ad.get("asking_price") else "N/A"
+        area = f"{ad.get('area_m2')}" if ad.get("area_m2") else "N/A"
+        price_sqm = (
+            f"{ad.get('asking_price') // ad.get('area_m2')}"
+            if ad.get("asking_price") and ad.get("area_m2")
+            else "N/A"
+        )
+        rooms = ad.get("rooms") or "N/A"
+        costs = f"{ad.get('common_costs'):,}" if ad.get("common_costs") else "N/A"
+        lines.append(f"| {addr} | {price} | {area} m² | {price_sqm} | {rooms} | {costs} |")
+
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Similar units renderer
+# ============================================================================
+
+
+def render_similar_units(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render similar/comparable units."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_similar_units_markdown(payload)
+    else:  # table
+        return _render_similar_units_table(payload)
+
+
+def _render_similar_units_markdown(data: dict[str, Any]) -> str:
+    """Render similar units as markdown."""
+    similar = data.get("similar_units", [])
+    lines = [
+        "# Similar/Comparable Units",
+        f"Found {len(similar)} comparable listings",
+        "",
+    ]
+    for i, unit in enumerate(similar, 1):
+        lines.extend(
+            [
+                f"## {i}. {unit.get('address', 'Unknown')}",
+                f"- **Listing Price:** {unit.get('listing_price'):,} NOK"
+                if unit.get("listing_price")
+                else "- **Listing Price:** N/A",
+                f"- **Selling Price:** {unit.get('selling_price'):,} NOK"
+                if unit.get("selling_price")
+                else "- **Selling Price:** N/A",
+                f"- **Area:** {unit.get('usable_area')} m²"
+                if unit.get("usable_area")
+                else "- **Area:** N/A",
+                f"- **Price/m²:** {unit.get('sqm_price'):,} NOK/m²"
+                if unit.get("sqm_price")
+                else "- **Price/m²:** N/A",
+                f"- **Days on Market:** {unit.get('days_on_market')}",
+                f"- **Status:** {unit.get('sale_status')}",
+                "",
+            ]
+        )
+    return "\n".join(lines)
+
+
+def _render_similar_units_table(data: dict[str, Any]) -> str:
+    """Render similar units as table."""
+    similar = data.get("similar_units", [])
+
+    lines = [
+        "| Address | Listing Price | Selling Price | Area | Price/m² | Days | Status |",
+        "|---------|---------------|---------------|------|----------|------|--------|",
+    ]
+
+    for unit in similar:
+        addr = (unit.get("address") or "")[:30]
+        list_price = f"{unit.get('listing_price'):,}" if unit.get("listing_price") else "N/A"
+        sell_price = f"{unit.get('selling_price'):,}" if unit.get("selling_price") else "N/A"
+        area = f"{unit.get('usable_area')}" if unit.get("usable_area") else "N/A"
+        price_sqm = f"{unit.get('sqm_price'):,}" if unit.get("sqm_price") else "N/A"
+        days = unit.get("days_on_market") or "N/A"
+        status = unit.get("sale_status") or "N/A"
+        lines.append(
+            f"| {addr} | {list_price} | {sell_price} | {area} m² | {price_sqm} | {days} | {status} |"
+        )
+
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Diff renderer
+# ============================================================================
+
+
+def render_diff(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render diff of new/removed/changed listings."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_diff_markdown(payload)
+    else:  # table
+        return _render_diff_table(payload)
+
+
+def _render_diff_markdown(data: dict[str, Any]) -> str:
+    """Render diff as markdown."""
+    new = data.get("new_ads", [])
+    removed = data.get("removed_ads", [])
+    changed = data.get("changed_ads", [])
+
+    lines = [
+        "# Listing Diff",
+        "",
+    ]
+
+    if new:
+        lines.extend(
+            [
+                f"## 🆕 New Listings ({len(new)})",
+                "",
+            ]
+        )
+        for ad in new:
+            lines.extend(
+                [
+                    f"- {ad.get('title', 'Unknown')} ({ad.get('address')})",
+                    f"  - Price: {ad.get('asking_price'):,} NOK"
+                    if ad.get("asking_price")
+                    else "  - Price: N/A",
+                    "",
+                ]
+            )
+
+    if removed:
+        lines.extend(
+            [
+                f"## ❌ Removed Listings ({len(removed)})",
+                "",
+            ]
+        )
+        for ad in removed:
+            lines.extend(
+                [
+                    f"- {ad.get('title', 'Unknown')} ({ad.get('address')})",
+                    "",
+                ]
+            )
+
+    if changed:
+        lines.extend(
+            [
+                f"## 🔄 Changed Listings ({len(changed)})",
+                "",
+            ]
+        )
+        for change in changed:
+            lines.extend(
+                [
+                    f"- {change.get('title', 'Unknown')} ({change.get('address')})",
+                ]
+            )
+            diffs = change.get("diffs", {})
+            for key, (old, new_val) in diffs.items():
+                lines.append(f"  - {key}: {old} → {new_val}")
+            lines.append("")
+
+    return "\n".join(lines)
+
+
+def _render_diff_table(data: dict[str, Any]) -> str:
+    """Render diff as table."""
+    new = data.get("new_ads", [])
+    removed = data.get("removed_ads", [])
+    changed = data.get("changed_ads", [])
+
+    lines = [
+        "| Type | Address | Price | Status |",
+        "|------|---------|-------|--------|",
+    ]
+
+    for ad in new:
+        addr = (ad.get("address") or "")[:30]
+        price = f"{ad.get('asking_price'):,}" if ad.get("asking_price") else "N/A"
+        lines.append(f"| 🆕 New | {addr} | {price} | - |")
+
+    for ad in removed:
+        addr = (ad.get("address") or "")[:30]
+        lines.append(f"| ❌ Removed | {addr} | - | - |")
+
+    for change in changed:
+        addr = (change.get("address") or "")[:30]
+        diffs = change.get("diffs", {})
+        changed_fields = ", ".join(diffs.keys())
+        lines.append(f"| 🔄 Changed | {addr} | - | {changed_fields} |")
+
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Score breakdown renderer
+# ============================================================================
+
+
+def render_score_breakdown(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render score breakdown details."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    else:
+        return _render_score_breakdown_markdown(payload)
+
+
+def _render_score_breakdown_markdown(data: dict[str, Any]) -> str:
+    """Render score breakdown as markdown."""
+    scores = data.get("scores", {})
+    lines = [
+        "# Score Breakdown",
+        "",
+    ]
+
+    for key, value in scores.items():
+        lines.append(f"- **{key}:** {value}")
+
+    return "\n".join(lines)
+
+
+# ============================================================================
+# Cache stats renderer
+# ============================================================================
+
+
+def render_cache_stats(payload: dict[str, Any], fmt: OutputFormat) -> str:
+    """Render cache statistics."""
+    _validate_format(fmt)
+
+    if fmt == "json":
+        return json.dumps(payload, indent=2, default=str)
+    elif fmt == "markdown":
+        return _render_cache_stats_markdown(payload)
+    else:  # table
+        return _render_cache_stats_table(payload)
+
+
+def _render_cache_stats_markdown(data: dict[str, Any]) -> str:
+    """Render cache stats as markdown."""
+    lines = [
+        "# Cache Statistics",
+        "",
+        f"- **Total FINN Ads:** {data.get('total_finn_ads', 0)}",
+        f"- **Total Eiendom Units:** {data.get('total_eiendom_units', 0)}",
+        f"- **Total Search Runs:** {data.get('total_search_runs', 0)}",
+        f"- **Cache Size:** {data.get('cache_size_mb', 0):.2f} MB",
+        f"- **Last Updated:** {data.get('last_updated')}",
+    ]
+    return "\n".join(lines)
+
+
+def _render_cache_stats_table(data: dict[str, Any]) -> str:
+    """Render cache stats as table."""
+    lines = [
+        "| Metric | Value |",
+        "|--------|-------|",
+        f"| Total FINN Ads | {data.get('total_finn_ads', 0)} |",
+        f"| Total Eiendom Units | {data.get('total_eiendom_units', 0)} |",
+        f"| Total Search Runs | {data.get('total_search_runs', 0)} |",
+        f"| Cache Size | {data.get('cache_size_mb', 0):.2f} MB |",
+        f"| Last Updated | {data.get('last_updated')} |",
+    ]
+    return "\n".join(lines)

finn_eiendom/mcp_server.py

@@ -2,6 +2,7 @@
 
 import json
 import logging
+from typing import Any
 
 from mcp.server.fastmcp import FastMCP
 
@@ -13,7 +14,24 @@ from .eiendom_no import (
     get_unit,
     search_unit_from_finn_url,
 )
-from .service import get_or_fetch_ad, get_or_fetch_eiendom_unit
+from .formatting import (
+    render_ad,
+    render_comparison,
+    render_diff,
+    render_shortlist,
+    render_similar_units,
+)
+from .service import (
+    analyze_ad,
+    analyze_ad_against_comps,
+    compare_ads,
+    find_similar_to_liked,
+    get_new_ads_since_last_run,
+    get_or_fetch_ad,
+    get_or_fetch_eiendom_unit,
+    get_shortlist,
+    save_feedback,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -151,6 +169,132 @@ def finn_decode_unit_vector(unit_vector: str) -> str:
         return json.dumps({"error": True, "message": str(e)})
 
 
+# ============================================================================
+# Additional analysis and enrichment tools
+# ============================================================================
+
+
+@mcp.tool(
+    description=(
+        "Fetch and enrich a single FINN ad with optional Eiendom.no data and comparable units."
+    )
+)
+async def finn_analyze_ad(
+    finnkode: str,
+    include_eiendom_no: bool = True,
+    include_similar_units: bool = False,
+) -> str:
+    """Analyze and enrich a single FINN ad."""
+    try:
+        result = await analyze_ad(
+            finnkode,
+            include_eiendom_no=include_eiendom_no,
+            include_similar_units=include_similar_units,
+        )
+        return render_ad(result.get("ad", {}), "json")
+    except Exception as e:
+        logger.error(f"Error analyzing ad {finnkode}: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(
+    description=(
+        "Evaluate one FINN listing against comparable recently-sold properties from Eiendom.no."
+    )
+)
+async def finn_analyze_ad_against_comps(
+    finnkode: str, listing_status: str = "RECENTLY_SOLD"
+) -> str:
+    """Analyze ad against comparable sales."""
+    try:
+        result = await analyze_ad_against_comps(finnkode, listing_status=listing_status)
+        return json.dumps(result, default=str)
+    except Exception as e:
+        logger.error(f"Error analyzing ad {finnkode} against comps: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(
+    description=(
+        "Find properties similar to a listing the user has liked. "
+        "Requires that the user has marked the listing with verdict='liked'."
+    )
+)
+async def finn_find_similar_to_liked_ad(
+    finnkode: str, mode: str = "recommendations", listing_status: str = "FOR_SALE"
+) -> str:
+    """Find properties similar to a liked ad."""
+    try:
+        result = await find_similar_to_liked(finnkode, mode=mode, listing_status=listing_status)
+        return render_similar_units(result, "json")
+    except Exception as e:
+        logger.error(f"Error finding similar to {finnkode}: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(description="Compare multiple FINN listings side by side with optional enrichment.")
+async def finn_compare_ads(
+    finnkoder: list[str],
+    include_eiendom_no: bool = True,
+    include_comps: bool = True,
+) -> str:
+    """Compare multiple ads."""
+    try:
+        result = await compare_ads(
+            finnkoder,
+            include_eiendom_no=include_eiendom_no,
+            include_comps=include_comps,
+        )
+        return render_comparison(result, "json")
+    except Exception as e:
+        logger.error(f"Error comparing ads: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(
+    description="Store user feedback (verdict, notes) for a FINN listing. "
+    "Enables similar-unit recommendations and shortlist filtering."
+)
+async def finn_save_feedback(finnkode: str, verdict: str, notes: str | None = None) -> str:
+    """Save user feedback for a listing."""
+    try:
+        result = save_feedback(finnkode, verdict, notes)
+        return json.dumps(result, default=str)
+    except Exception as e:
+        logger.error(f"Error saving feedback for {finnkode}: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(
+    description="Fetch the stored shortlist from a previous search run. "
+    "Returns the ranked listings with all enrichment data."
+)
+def finn_get_shortlist(run_id: int | None = None, limit: int = 10) -> str:
+    """Get stored shortlist."""
+    try:
+        result = get_shortlist(run_id, limit)
+        return render_shortlist(result, "json")
+    except Exception as e:
+        logger.error(f"Error fetching shortlist: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
+@mcp.tool(
+    description=(
+        "Detect new, removed, and changed listings in a FINN search URL "
+        "compared to the previous run. Shows price/status diffs on changed listings."
+    )
+)
+async def finn_get_new_ads_since_last_run(search_url: str) -> str:
+    """Get new/removed/changed listings since last run."""
+    try:
+        result = get_new_ads_since_last_run(search_url)
+        return render_diff(result, "json")
+    except Exception as e:
+        logger.error(f"Error fetching diff: {e}")
+        return json.dumps({"error": True, "message": str(e)})
+
+
 def main() -> None:
     """Run the FastMCP stdio server."""
     mcp.run(transport="stdio")

finn_eiendom/models.py

@@ -60,7 +60,7 @@ class FinnAd(BaseModel):
     detail_fetched_at: datetime | None = None
     eiendom_unit_code: str | None = None
 
-    model_config = ConfigDict(serializers={datetime: lambda v: v.isoformat()})
+    model_config = ConfigDict()
 
 
 class EiendomUnit(BaseModel):
@@ -87,7 +87,7 @@ class EiendomUnit(BaseModel):
     unit_vector: str | None = None
     fetched_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
 
-    model_config = ConfigDict(serializers={datetime: lambda v: v.isoformat()})
+    model_config = ConfigDict()
 
 
 class SimilarUnit(BaseModel):
@@ -112,7 +112,7 @@ class SimilarUnit(BaseModel):
     finalized_at: datetime | None = None
     listing_status: str = Field(default="RECENTLY_SOLD")
 
-    model_config = ConfigDict(serializers={datetime: lambda v: v.isoformat() if v else None})
+    model_config = ConfigDict()
 
 
 class UnitVector(BaseModel):

finn_eiendom/service.py

@@ -1,13 +1,27 @@
 """Service layer for cache-aware fetching of FINN ads and Eiendom.no units."""
 
 import logging
+from typing import Any
 
 from .ad import fetch_ad_details
-from .cache import get_eiendom_unit as get_cached_eiendom_unit
-from .cache import get_finn_ad, init_db, save_eiendom_unit, save_finn_ad
+from .analysis import analyze_search as run_analysis_search
+from .cache import (
+    get_eiendom_unit as get_cached_eiendom_unit,
+    get_finn_ad,
+    init_db,
+    save_eiendom_unit,
+    save_finn_ad,
+)
 from .config import FINN_CACHE_PATH
-from .eiendom_no import get_unit
-from .models import EiendomUnit, FinnAd
+from .eiendom_no import (
+    build_unit_vector,
+    decode_unit_vector,
+    get_similar_units,
+    get_unit,
+    search_unit_from_finn_url,
+)
+from .feedback import save_feedback as save_feedback_impl
+from .models import EiendomUnit, FinnAd, SimilarUnit
 
 logger = logging.getLogger(__name__)
 
@@ -33,3 +47,162 @@ async def get_or_fetch_eiendom_unit(
         if unit is not None:
             save_eiendom_unit(conn, unit)
     return unit
+
+
+async def get_or_fetch_similar_units(
+    unit_code: str, listing_status: str = "RECENTLY_SOLD", force_refresh: bool = False
+) -> list[SimilarUnit]:
+    """Get similar units (comps) from cache or fetch fresh."""
+    # Similar units don't have a separate cache table; fetch fresh each time per PRD
+    # (or cache them in search_runs if doing diff detection)
+    return await get_similar_units(unit_code, listing_status=listing_status)
+
+
+async def resolve_eiendom_unit_from_finn_url(finn_url: str) -> EiendomUnit | None:
+    """Resolve an Eiendom.no unit from a FINN listing URL."""
+    return await search_unit_from_finn_url(finn_url)
+
+
+# ============================================================================
+# Orchestration functions — delegate to analysis.py
+# ============================================================================
+
+
+async def analyze_search(
+    search_url: str,
+    *,
+    max_pages: int = 3,
+    detail_limit: int = 20,
+    include_details: bool = True,
+    include_eiendom_no: bool = True,
+    include_similar_units_for_shortlist: bool = False,
+) -> dict[str, Any]:
+    """Analyze a FINN search URL and return a ranked shortlist."""
+    return await run_analysis_search(
+        search_url,
+        max_pages=max_pages,
+        fetch_details=include_details,
+        detail_limit=detail_limit,
+        include_eiendom_no=include_eiendom_no,
+        include_similar_units_for_shortlist=include_similar_units_for_shortlist,
+    )
+
+
+async def analyze_ad(
+    finnkode: str,
+    *,
+    include_eiendom_no: bool = True,
+    include_similar_units: bool = False,
+) -> dict[str, Any]:
+    """Fetch and enrich a single FINN ad with analysis."""
+    ad = await get_or_fetch_ad(finnkode)
+    result: dict[str, Any] = {
+        "ad": ad.model_dump(),
+    }
+    if include_eiendom_no and ad.eiendom_unit_code:
+        unit = await get_or_fetch_eiendom_unit(ad.eiendom_unit_code)
+        if unit:
+            result["eiendom_unit"] = unit.model_dump()
+            if include_similar_units:
+                similar = await get_or_fetch_similar_units(ad.eiendom_unit_code)
+                result["similar_units"] = [s.model_dump() for s in similar]
+    return result
+
+
+async def analyze_ad_against_comps(
+    finnkode: str, listing_status: str = "RECENTLY_SOLD"
+) -> dict[str, Any]:
+    """Evaluate one listing against recent comparable sales."""
+    ad = await get_or_fetch_ad(finnkode)
+    result: dict[str, Any] = {
+        "ad": ad.model_dump(),
+    }
+    if ad.eiendom_unit_code:
+        unit = await get_or_fetch_eiendom_unit(ad.eiendom_unit_code)
+        if unit:
+            result["eiendom_unit"] = unit.model_dump()
+            comps = await get_or_fetch_similar_units(
+                ad.eiendom_unit_code, listing_status=listing_status
+            )
+            result["comparable_units"] = [c.model_dump() for c in comps]
+    return result
+
+
+async def find_similar_to_liked(
+    finnkode: str, *, mode: str = "recommendations", listing_status: str = "FOR_SALE"
+) -> dict[str, Any]:
+    """Find properties similar to a listing the user has liked."""
+    # Requires that feedback.verdict = "liked" exists for this finnkode
+    ad = await get_or_fetch_ad(finnkode)
+    if not ad.eiendom_unit_code:
+        raise ValueError(
+            f"Finnkode {finnkode} has no Eiendom.no unit_code; cannot find similar properties"
+        )
+
+    # TODO: verify feedback verdict = "liked" exists
+    unit = await get_or_fetch_eiendom_unit(ad.eiendom_unit_code)
+    if not unit:
+        raise ValueError(f"Cannot enrich finnkode {finnkode} with Eiendom.no data")
+
+    similar = await get_or_fetch_similar_units(ad.eiendom_unit_code, listing_status=listing_status)
+    return {
+        "base_ad": ad.model_dump(),
+        "similar_listings": [s.model_dump() for s in similar],
+        "mode": mode,
+    }
+
+
+async def compare_ads(
+    finnkoder: list[str], *, include_eiendom_no: bool = True, include_comps: bool = True
+) -> dict[str, Any]:
+    """Compare multiple FINN listings side by side."""
+    ads = []
+    for finnkode in finnkoder:
+        ad = await get_or_fetch_ad(finnkode)
+        ad_data = ad.model_dump()
+
+        if include_eiendom_no and ad.eiendom_unit_code:
+            unit = await get_or_fetch_eiendom_unit(ad.eiendom_unit_code)
+            if unit:
+                ad_data["eiendom_unit"] = unit.model_dump()
+                if include_comps:
+                    comps = await get_or_fetch_similar_units(
+                        ad.eiendom_unit_code, listing_status="RECENTLY_SOLD"
+                    )
+                    ad_data["comps"] = [c.model_dump() for c in comps]
+
+        ads.append(ad_data)
+
+    return {"listings": ads}
+
+
+# ============================================================================
+# Helper functions
+# ============================================================================
+
+
+def build_unit_vector_for_unit_code(unit_code: str) -> dict[str, Any]:
+    """Build a unit_vector dict for a unit_code (msgpack-encoded)."""
+    return build_unit_vector(unit_code)
+
+
+def decode_unit_vector_to_dict(unit_vector: str) -> dict[str, Any]:
+    """Decode a unit_vector string to a dict."""
+    return decode_unit_vector(unit_vector)
+
+
+def save_feedback(finnkode: str, verdict: str, notes: str | None = None) -> dict[str, Any]:
+    """Store user feedback/verdict for a listing."""
+    return save_feedback_impl(finnkode, verdict, notes)
+
+
+def get_shortlist(run_id: int | None = None, limit: int = 10) -> dict[str, Any]:
+    """Fetch stored shortlist from a search run."""
+    # TODO: implement via search_runs table in cache.py
+    return {"shortlist": [], "run_id": run_id, "limit": limit}
+
+
+def get_new_ads_since_last_run(search_url: str) -> dict[str, Any]:
+    """Detect new/removed/changed listings vs the previous run."""
+    # TODO: implement via search_runs table in cache.py
+    return {"new_ads": [], "removed_ads": [], "changed_ads": [], "search_url": search_url}

pyproject.toml

@@ -16,6 +16,7 @@ dependencies = [
 ]
 
 [project.scripts]
+finn-eiendom = "finn_eiendom.cli:app"
 finn-eiendom-mcp = "finn_eiendom.mcp_server:main"
 
 [dependency-groups]

tests/test_formatting.py

@@ -0,0 +1,172 @@
+"""Tests for formatting module."""
+
+import pytest
+
+from finn_eiendom import formatting
+
+
+def test_render_ad_json():
+    """Test rendering ad as JSON."""
+    ad = {
+        "finnkode": "123456",
+        "title": "Nice apartment",
+        "address": "Hovedstreet 1",
+        "asking_price": 5000000,
+        "area_m2": 80,
+    }
+    result = formatting.render_ad(ad, "json")
+    assert "123456" in result
+    assert "Nice apartment" in result
+    assert isinstance(result, str)
+
+
+def test_render_ad_markdown():
+    """Test rendering ad as Markdown."""
+    ad = {
+        "finnkode": "123456",
+        "title": "Nice apartment",
+        "address": "Hovedstreet 1",
+        "asking_price": 5000000,
+        "area_m2": 80,
+    }
+    result = formatting.render_ad(ad, "markdown")
+    assert "Nice apartment" in result
+    assert "Hovedstreet 1" in result
+    assert "#" in result  # Markdown headers
+
+
+def test_render_shortlist_json():
+    """Test rendering shortlist as JSON."""
+    data = {
+        "shortlist": [
+            {
+                "finnkode": "1",
+                "title": "Ad 1",
+                "address": "Street 1",
+                "asking_price": 5000000,
+                "area_m2": 80,
+            },
+            {
+                "finnkode": "2",
+                "title": "Ad 2",
+                "address": "Street 2",
+                "asking_price": 4500000,
+                "area_m2": 75,
+            },
+        ]
+    }
+    result = formatting.render_shortlist(data, "json")
+    assert "Ad 1" in result
+    assert "Ad 2" in result
+
+
+def test_render_shortlist_markdown():
+    """Test rendering shortlist as Markdown."""
+    data = {
+        "shortlist": [
+            {
+                "finnkode": "1",
+                "title": "Ad 1",
+                "address": "Street 1",
+                "asking_price": 5000000,
+                "area_m2": 80,
+            },
+        ]
+    }
+    result = formatting.render_shortlist(data, "markdown")
+    assert "Ad 1" in result
+    assert "Street 1" in result
+
+
+def test_render_shortlist_table():
+    """Test rendering shortlist as table."""
+    data = {
+        "shortlist": [
+            {
+                "finnkode": "1",
+                "title": "Ad 1",
+                "address": "Street 1",
+                "asking_price": 5000000,
+                "area_m2": 80,
+            },
+        ]
+    }
+    result = formatting.render_shortlist(data, "table")
+    assert "|" in result  # Table format
+
+
+def test_render_comparison():
+    """Test rendering comparison."""
+    data = {
+        "listings": [
+            {
+                "finnkode": "1",
+                "title": "Ad 1",
+                "address": "Street 1",
+                "asking_price": 5000000,
+                "area_m2": 80,
+            },
+            {
+                "finnkode": "2",
+                "title": "Ad 2",
+                "address": "Street 2",
+                "asking_price": 4500000,
+                "area_m2": 75,
+            },
+        ]
+    }
+    result = formatting.render_comparison(data, "markdown")
+    assert "Comparison" in result
+    assert "Ad 1" in result
+    assert "Ad 2" in result
+
+
+def test_render_diff():
+    """Test rendering diff."""
+    data = {
+        "new_ads": [
+            {
+                "title": "New Ad",
+                "address": "New Street",
+                "asking_price": 5000000,
+            },
+        ],
+        "removed_ads": [],
+        "changed_ads": [],
+    }
+    result = formatting.render_diff(data, "markdown")
+    assert "New" in result
+    assert "New Ad" in result
+
+
+def test_render_cache_stats():
+    """Test rendering cache stats."""
+    data = {
+        "total_finn_ads": 100,
+        "total_eiendom_units": 50,
+        "total_search_runs": 10,
+        "cache_size_mb": 25.5,
+        "last_updated": "2024-01-01",
+    }
+    result = formatting.render_cache_stats(data, "json")
+    assert "100" in result
+    assert "50" in result
+
+
+def test_format_validation():
+    """Test that invalid formats raise ValueError."""
+    with pytest.raises(ValueError):
+        formatting.render_ad({}, "invalid")
+
+
+def test_render_unit():
+    """Test rendering Eiendom unit."""
+    unit = {
+        "unit_code": "code123",
+        "address": "Hovedstreet 1",
+        "rooms": 3,
+        "estimated_selling_price": 5000000,
+    }
+    result = formatting.render_unit(unit, "markdown")
+    assert "Hovedstreet 1" in result
+    assert "3" in result

tests/test_models.py

@@ -0,0 +1,265 @@
+"""Tests for Pydantic models in finn_eiendom.models."""
+
+import json
+from datetime import UTC, datetime
+
+from finn_eiendom.models import (
+    EiendomUnit,
+    FinnAd,
+    FinnSearchCard,
+    SimilarUnit,
+    UnitVector,
+)
+
+
+def test_finn_search_card_json_roundtrip():
+    """Test JSON roundtrip for FinnSearchCard model."""
+    data = {
+        "finnkode": "123456789",
+        "url": "https://www.finn.no/realestate/homes/ad.html?finnkode=123456789",
+        "title": "Beautiful apartment in Oslo",
+        "address": "Karl Johans gate 1",
+        "area_m2": 80,
+        "asking_price": 5000000,
+        "total_price": 5200000,
+        "common_costs": 2000,
+        "property_type": "APARTMENT",
+        "ownership_type": "FREEHOLD",
+        "bedrooms": 2,
+        "floor": "3/5",
+        "broker_company": "Estate AS",
+    }
+
+    # Create model instance
+    model = FinnSearchCard(**data)
+
+    # Convert to JSON
+    json_str = model.model_dump_json()
+
+    # Parse JSON back to dict
+    parsed_data = json.loads(json_str)
+
+    # Create new instance from parsed data
+    model_from_json = FinnSearchCard(**parsed_data)
+
+    # Assert they're equal
+    assert model == model_from_json
+
+
+def test_finn_ad_json_roundtrip():
+    """Test JSON roundtrip for FinnAd model."""
+    now = datetime.now(UTC)
+    data = {
+        "finnkode": "123456789",
+        "url": "https://www.finn.no/realestate/homes/ad.html?finnkode=123456789",
+        "title": "Beautiful apartment in Oslo",
+        "address": "Karl Johans gate 1",
+        "postal_area": "0150",
+        "district": "Sentrum",
+        "property_type": "APARTMENT",
+        "ownership_type": "FREEHOLD",
+        "asking_price": 5000000,
+        "total_price": 5200000,
+        "shared_debt": 100000,
+        "common_costs": 2000,
+        "municipal_fee": 500,
+        "other_fees": 300,
+        "area_m2": 80,
+        "rooms": 3,
+        "bedrooms": 2,
+        "floor": "3/5",
+        "construction_year": 2000,
+        "energy_rating": "C",
+        "heating": "FJERNVARME",
+        "has_balcony": True,
+        "has_terrace": False,
+        "has_elevator": True,
+        "has_parking": False,
+        "has_garage": False,
+        "listing_description": "A lovely apartment with great views",
+        "broker_name": "John Doe",
+        "broker_company": "Estate AS",
+        "first_seen_at": now,
+        "last_seen_at": now,
+        "detail_fetched_at": now,
+        "eiendom_unit_code": "EI-987654321",
+    }
+
+    # Create model instance
+    model = FinnAd(**data)
+
+    # Convert to JSON
+    json_str = model.model_dump_json()
+
+    # Parse JSON back to dict
+    parsed_data = json.loads(json_str)
+
+    # Create new instance from parsed data
+    model_from_json = FinnAd(**parsed_data)
+
+    # Assert they're equal
+    assert model == model_from_json
+
+
+def test_eiendom_unit_json_roundtrip():
+    """Test JSON roundtrip for EiendomUnit model."""
+    now = datetime.now(UTC)
+    data = {
+        "unit_code": "EI-987654321",
+        "address": "Karl Johans gate 1",
+        "lat": 59.9139,
+        "lng": 10.7522,
+        "property_type": "APARTMENT",
+        "floor": 3,
+        "rooms": 3,
+        "construction_year": 2000,
+        "usable_area": 80,
+        "estimated_selling_price": 5500000,
+        "estimated_selling_price_lower": 5200000,
+        "estimated_selling_price_upper": 5800000,
+        "listing_price": 5000000,
+        "listing_sqm_price": 62500,
+        "common_costs": 2000,
+        "days_on_market": 45,
+        "sale_status": "FOR_SALE",
+        "market_placement_score": "GOOD",
+        "unit_vector": "base64encodedvector===",
+        "fetched_at": now,
+    }
+
+    # Create model instance
+    model = EiendomUnit(**data)
+
+    # Convert to JSON
+    json_str = model.model_dump_json()
+
+    # Parse JSON back to dict
+    parsed_data = json.loads(json_str)
+
+    # Create new instance from parsed data
+    model_from_json = EiendomUnit(**parsed_data)
+
+    # Assert they're equal
+    assert model == model_from_json
+
+
+def test_similar_unit_json_roundtrip():
+    """Test JSON roundtrip for SimilarUnit model."""
+    data = {
+        "unit_code": "EI-123456789",
+        "address": "Karl Johans gate 2",
+        "lat": 59.9140,
+        "lng": 10.7523,
+        "property_type": "APARTMENT",
+        "floor": 4,
+        "rooms": 3,
+        "construction_year": 2005,
+        "usable_area": 90,
+        "listing_price": 5800000,
+        "selling_price": 5700000,
+        "shared_debt": 120000,
+        "common_costs": 2200,
+        "sqm_price": 63333,
+        "days_on_market": 30,
+        "sale_status": "SOLD",
+        "finalized_at": datetime.now(UTC),
+        "listing_status": "RECENTLY_SOLD",
+    }
+
+    # Create model instance
+    model = SimilarUnit(**data)
+
+    # Convert to JSON
+    json_str = model.model_dump_json()
+
+    # Parse JSON back to dict
+    parsed_data = json.loads(json_str)
+
+    # Create new instance from parsed data
+    model_from_json = SimilarUnit(**parsed_data)
+
+    # Assert they're equal
+    assert model == model_from_json
+
+
+def test_unit_vector_json_roundtrip():
+    """Test JSON roundtrip for UnitVector model."""
+    data = {
+        "lon": 10.7522,
+        "lat": 59.9139,
+        "ptype": "APARTMENT",
+        "floor": 3,
+        "rooms": 3,
+        "built": 2000,
+        "area": 80,
+        "price": 5000000,
+    }
+
+    # Create model instance
+    model = UnitVector(**data)
+
+    # Convert to JSON
+    json_str = model.model_dump_json()
+
+    # Parse JSON back to dict
+    parsed_data = json.loads(json_str)
+
+    # Create new instance from parsed data
+    model_from_json = UnitVector(**parsed_data)
+
+    # Assert they're equal
+    assert model == model_from_json
+
+
+def test_finn_ad_serializer_datetime():
+    """Test that FinnAd datetime serialization works correctly."""
+    now = datetime.now(UTC)
+    data = {
+        "finnkode": "123456789",
+        "url": "https://www.finn.no/realestate/homes/ad.html?finnkode=123456789",
+        "first_seen_at": now,
+        "last_seen_at": now,
+    }
+
+    model = FinnAd(**data)
+    json_str = model.model_dump_json()
+    parsed_data = json.loads(json_str)
+
+    # Check that datetimes are serialized as ISO strings
+    assert isinstance(parsed_data["first_seen_at"], str)
+    assert isinstance(parsed_data["last_seen_at"], str)
+    assert "T" in parsed_data["first_seen_at"]  # ISO format contains T
+    assert "Z" in parsed_data["first_seen_at"] or "+" in parsed_data["first_seen_at"]  # TZ info
+
+
+def test_eiendom_unit_serializer_datetime():
+    """Test that EiendomUnit datetime serialization works correctly."""
+    now = datetime.now(UTC)
+    data = {
+        "unit_code": "EI-987654321",
+        "fetched_at": now,
+    }
+
+    model = EiendomUnit(**data)
+    json_str = model.model_dump_json()
+    parsed_data = json.loads(json_str)
+
+    # Check that datetimes are serialized as ISO strings
+    assert isinstance(parsed_data["fetched_at"], str)
+    assert "T" in parsed_data["fetched_at"]  # ISO format contains T
+    assert "Z" in parsed_data["fetched_at"] or "+" in parsed_data["fetched_at"]  # Timezone info
+
+
+def test_similar_unit_serializer_datetime():
+    """Test that SimilarUnit datetime serialization works correctly (handles None)."""
+    data = {
+        "unit_code": "EI-123456789",
+        "finalized_at": None,  # This should serialize to null
+    }
+
+    model = SimilarUnit(**data)
+    json_str = model.model_dump_json()
+    parsed_data = json.loads(json_str)
+
+    # Check that None datetimes serialize to null
+    assert parsed_data["finalized_at"] is None