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finn-mcp/.github/instructions/mcp.instructions.md
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---
name: MCP rules
description: Rules for FastMCP tools, resources, and prompts
applyTo: "finn_eiendom/mcp_server.py,finn_eiendom/**/*mcp*.py"
---
# MCP server rules
The MCP server is a **thin wrapper** over `service.py`. It owns:
* Tool registration with `@mcp.tool()` and annotations.
* Pydantic input schemas (these double as tool documentation).
* Error wrapping at the protocol boundary.
* JSON / markdown response formatting via `formatting.py`.
It does **not** own:
* Parsing, scraping, scoring, cache, or HTTP fetching logic.
* SQLite or `httpx` access.
* Any orchestration of "check cache, else fetch, else save" — that's `service.py`.
## Server bootstrap
```python
# finn_eiendom/mcp_server.py
import sys, logging
from mcp.server.fastmcp import FastMCP
logging.basicConfig(stream=sys.stderr, level=logging.INFO,
format="%(asctime)s %(levelname)s %(name)s %(message)s")
mcp = FastMCP("finn_eiendom_mcp")
# ... tools registered here ...
def main() -> None:
mcp.run(transport="stdio")
if __name__ == "__main__":
main()
```
stdio servers **must** log to stderr only — anything on stdout breaks the JSON-RPC frame.
## Tool naming
All tools use the `finn_` prefix so they don't collide with other MCP servers running in the same Claude Desktop:
* `finn_analyze_search`
* `finn_get_ad`
* `finn_compare_ads`
* `finn_save_feedback`
* `finn_get_shortlist`
* `finn_get_new_ads_since_last_run`
* `finn_resolve_eiendom_unit`
* `finn_get_eiendom_unit`
* `finn_enrich_ad`
* `finn_build_unit_vector`
* `finn_decode_unit_vector`
* `finn_get_similar_units`
* `finn_find_similar_to_liked_ad`
* `finn_analyze_ad_against_comps`
## Tool body shape
Every tool body looks like this:
```python
@mcp.tool(
annotations=ToolAnnotations(
title="Analyze a FINN search URL",
readOnlyHint=True,
destructiveHint=False,
openWorldHint=True,
)
)
async def finn_analyze_search(input: AnalyzeSearchInput) -> str:
"""Analyze a FINN search URL and return a ranked shortlist."""
try:
result = await service.analyze_search(
search_url=input.search_url,
max_pages=input.max_pages,
detail_limit=input.detail_limit,
include_details=input.include_details,
include_eiendom_no=input.include_eiendom_no,
include_similar_units_for_shortlist=input.include_similar_units_for_shortlist,
)
return formatting.render_shortlist(result, input.response_format)
except Exception as e:
log.exception("finn_analyze_search failed")
return json.dumps({
"error": True,
"code": type(e).__name__,
"message": str(e),
})
```
Notes:
* Every tool delegates to `service.<function>` in one call.
* Every tool wraps in try/except and returns the error envelope as a JSON string.
* Output rendering goes through `formatting.py`, never inline.
* If the tool body needs more than ~20 lines, logic has leaked out of the service layer — push it back down.
## Input schemas
Every tool has a Pydantic v2 input model. Schemas live with the tool in `mcp_server.py` (they document the tool to LLM clients). Reuse from `models.py` only when the same shape is also a domain object — otherwise keep them as tool-local input types.
```python
class AnalyzeSearchInput(BaseModel):
search_url: str = Field(..., description="Full FINN search URL")
max_pages: int = Field(default=3, ge=1, le=10)
detail_limit: int = Field(default=20, ge=1, le=100)
include_details: bool = True
include_eiendom_no: bool = True
include_similar_units_for_shortlist: bool = False
response_format: Literal["json", "markdown"] = "json"
```
## Annotations
Set the right hints:
* Read-only tools (most of them): `readOnlyHint=True, destructiveHint=False, openWorldHint=True`.
* `finn_save_feedback`: `readOnlyHint=False, destructiveHint=False, idempotentHint=False`.
## Response format
Tools accept a `response_format` parameter (`"json"` or `"markdown"`):
* `"json"` — return `json.dumps(result_dict)`.
* `"markdown"` — return `formatting.render_<thing>(result, "markdown")`.
Errors are always returned as the JSON error envelope regardless of `response_format`.
## What stays out of mcp_server.py
* `import httpx` — never.
* `import sqlite3` — never.
* `from .ad import ...`, `from .search import ...`, `from .eiendom_no import ...`, `from .scoring import ...`, `from .cache import ...`, `from .http import ...` — never. Go through `service`.
* Output formatting logic — goes in `formatting.py`.
* Cache management — goes in `service.py`.
Allowed imports in `mcp_server.py`:
```python
import json, logging, sys
from typing import Literal, Optional
from mcp.server.fastmcp import FastMCP
from mcp.server.fastmcp.utilities import ToolAnnotations
from pydantic import BaseModel, Field
from . import service, formatting
from .models import FinnAd, EiendomUnit, SimilarUnit # only if needed for type hints
from . import config
```
`tests/test_architecture.py` enforces this.
## Resources and prompts
When you add resources or prompts, they follow the same rule: thin wrappers over `service.py` and `formatting.py`. Resources:
```
finn://preferences/current
finn://search-runs/latest
finn://search-runs/{id}
finn://ads/{finnkode}
finn://ads/{finnkode}/enriched
finn://shortlist/latest
finn://feedback/{finnkode}
finn://eiendom-units/{unitCode}
finn://eiendom-units/{unitCode}/similar/{listingStatus}
```
Prompts: `evaluate_property_for_user`, `compare_properties_for_user`, `refine_search_from_feedback`, `find_more_like_this`.
## When uncertain about FastMCP
Use `context7` for FastMCP / MCP SDK questions instead of guessing:
```
context7:resolve-library-id → "modelcontextprotocol/python-sdk" or similar
context7:query-docs(id, "FastMCP tool annotations") → snippets
```
See `docs.instructions.md`.
## Transports
* Default: stdio. `finn-eiendom-mcp` is the entry point.
* Optional: Streamable HTTP via `finn-eiendom serve --transport http --port 8010`. Path: `POST /mcp`. Operational endpoints: `GET /health`, `GET /version`, `GET /debug/config`.
* Keep tools transport-agnostic. No request/response shape depends on the transport.