feat(mcp): tools/ package + fable_search

Establishes the tool pattern: each tool module exposes register(mcp),
register_all() aggregates them, build_mcp_server() calls register_all.

fable_search mirrors the existing fable-mcp contract (q/content_type/limit
in; {results, total} out) but calls services.embeddings.semantic_search_notes
directly instead of going over HTTP. User comes from mcp.current_user_id().

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-26 20:18:36 -04:00
parent 3579db2f06
commit fd0431dfb6
4 changed files with 163 additions and 1 deletions
+2 -1
View File
@@ -24,7 +24,8 @@ Hierarchy: Project -> Milestone -> Task/Note.
def build_mcp_server() -> FastMCP:
"""Build the FastMCP instance with all tools registered."""
mcp = FastMCP("fable", instructions=_INSTRUCTIONS.strip())
# Tools will be registered here in Phase 2/3.
from fabledassistant.mcp.tools import register_all
register_all(mcp)
return mcp
+12
View File
@@ -0,0 +1,12 @@
"""MCP tool implementations.
Each tool module exposes a `register(mcp)` function that attaches its tools
to a FastMCP instance. `register_all(mcp)` is the single entry point called
from `mcp.server.build_mcp_server`.
"""
from fabledassistant.mcp.tools import search
def register_all(mcp) -> None:
"""Register every tool module's tools on the given FastMCP instance."""
search.register(mcp)
+49
View File
@@ -0,0 +1,49 @@
"""fable_search — semantic search across the user's notes and tasks.
Mirrors the existing fable-mcp contract so Claude's prior usage pattern keeps
working. Differences from fable-mcp:
- calls services.embeddings.semantic_search_notes directly instead of HTTP
- user_id comes from mcp.current_user_id() rather than a global API key
"""
from __future__ import annotations
from fabledassistant.mcp._context import current_user_id
from fabledassistant.services.embeddings import semantic_search_notes
async def fable_search(q: str, content_type: str = "all", limit: int = 10) -> dict:
"""Semantic search over the user's notes and tasks.
Args:
q: search query string.
content_type: 'all' (default), 'note' (notes only), or 'task' (tasks only).
limit: maximum number of results (1-50).
Returns:
{"results": [{"id", "title", "body", "is_task", "tags", "similarity"}],
"total": int}
"""
uid = current_user_id()
limit = max(1, min(limit, 50))
is_task = {"note": False, "task": True}.get(content_type) # None => any
raw = await semantic_search_notes(
uid, q, limit=limit, is_task=is_task,
)
return {
"results": [
{
"id": note.id,
"title": note.title,
"body": (note.body or "")[:240],
"is_task": bool(note.is_task),
"tags": list(note.tags or []),
"similarity": float(score),
}
for score, note in raw
],
"total": len(raw),
}
def register(mcp) -> None:
mcp.tool(name="fable_search")(fable_search)
+100
View File
@@ -0,0 +1,100 @@
"""fable_search tool — proves the tool pattern (context + service call + dict shape).
Service call is mocked; no DB needed."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from fabledassistant.mcp._context import _user_id_ctx
from fabledassistant.mcp.tools.search import fable_search
@pytest.fixture(autouse=True)
def _reset_user_ctx():
"""Each test starts with no MCP context. Tests set it explicitly."""
token = _user_id_ctx.set(None)
yield
_user_id_ctx.reset(token)
def _fake_note(*, id: int, title: str, body: str = "",
tags: list[str] | None = None, is_task: bool = False) -> MagicMock:
note = MagicMock()
note.id = id
note.title = title
note.body = body
note.tags = tags or []
note.is_task = is_task
return note
@pytest.mark.asyncio
async def test_fable_search_raises_without_context():
with pytest.raises(RuntimeError, match="no MCP user context"):
await fable_search(q="anything")
@pytest.mark.asyncio
async def test_fable_search_returns_repackaged_results():
_user_id_ctx.set(7)
fake = _fake_note(id=1, title="kafka rebalance", body="HPA details",
tags=["ops"], is_task=False)
with patch(
"fabledassistant.mcp.tools.search.semantic_search_notes",
AsyncMock(return_value=[(0.93, fake)]),
):
out = await fable_search(q="kafka")
assert out["total"] == 1
assert len(out["results"]) == 1
r = out["results"][0]
assert r["id"] == 1
assert r["title"] == "kafka rebalance"
assert r["body"] == "HPA details"
assert r["is_task"] is False
assert r["tags"] == ["ops"]
assert r["similarity"] == pytest.approx(0.93)
@pytest.mark.asyncio
async def test_fable_search_body_is_truncated_to_240_chars():
_user_id_ctx.set(7)
long_body = "x" * 500
fake = _fake_note(id=1, title="t", body=long_body)
with patch(
"fabledassistant.mcp.tools.search.semantic_search_notes",
AsyncMock(return_value=[(0.5, fake)]),
):
out = await fable_search(q="x")
assert len(out["results"][0]["body"]) == 240
@pytest.mark.asyncio
async def test_fable_search_content_type_filters_at_service_layer():
"""content_type maps to the is_task kwarg passed to the service."""
_user_id_ctx.set(7)
mock_search = AsyncMock(return_value=[])
with patch("fabledassistant.mcp.tools.search.semantic_search_notes", mock_search):
await fable_search(q="x", content_type="task")
assert mock_search.call_args.kwargs["is_task"] is True
mock_search.reset_mock()
await fable_search(q="x", content_type="note")
assert mock_search.call_args.kwargs["is_task"] is False
mock_search.reset_mock()
await fable_search(q="x", content_type="all")
assert mock_search.call_args.kwargs["is_task"] is None
@pytest.mark.asyncio
async def test_fable_search_limit_is_clamped():
_user_id_ctx.set(7)
mock_search = AsyncMock(return_value=[])
with patch("fabledassistant.mcp.tools.search.semantic_search_notes", mock_search):
await fable_search(q="x", limit=999)
assert mock_search.call_args.kwargs["limit"] == 50
mock_search.reset_mock()
await fable_search(q="x", limit=0)
assert mock_search.call_args.kwargs["limit"] == 1