bvandeusen
fd0431dfb6
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>
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
"""fable_search — semantic search across the user's notes and tasks.
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Mirrors the existing fable-mcp contract so Claude's prior usage pattern keeps
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working. Differences from fable-mcp:
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- calls services.embeddings.semantic_search_notes directly instead of HTTP
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- user_id comes from mcp.current_user_id() rather than a global API key
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"""
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from __future__ import annotations
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from fabledassistant.mcp._context import current_user_id
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from fabledassistant.services.embeddings import semantic_search_notes
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async def fable_search(q: str, content_type: str = "all", limit: int = 10) -> dict:
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"""Semantic search over the user's notes and tasks.
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Args:
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q: search query string.
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content_type: 'all' (default), 'note' (notes only), or 'task' (tasks only).
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limit: maximum number of results (1-50).
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Returns:
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{"results": [{"id", "title", "body", "is_task", "tags", "similarity"}],
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"total": int}
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"""
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uid = current_user_id()
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limit = max(1, min(limit, 50))
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is_task = {"note": False, "task": True}.get(content_type) # None => any
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raw = await semantic_search_notes(
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uid, q, limit=limit, is_task=is_task,
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)
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return {
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"results": [
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{
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"id": note.id,
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"title": note.title,
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"body": (note.body or "")[:240],
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"is_task": bool(note.is_task),
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"tags": list(note.tags or []),
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"similarity": float(score),
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}
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for score, note in raw
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],
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"total": len(raw),
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}
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def register(mcp) -> None:
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mcp.tool(name="fable_search")(fable_search)
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