memo
MCP server for local, offline-capable library documentation. It resolves library IDs and retrieves up-to-date docs via hybrid search from a persistent SQLite cache.
README
memo
MCP server lokal untuk dokumentasi library versi-terbaru — klon Context7 yang gratis total, unlimited, dan offline-capable. Index dibangun on-demand ke SQLite (BM25 + vektor) dari llms.txt / halaman docs resmi.
Fitur
resolve_library_id(name, query)— resolusi library → kandidat {repo, docs_url, trust}: alias kurasi manual → builtin stdlib (Node/Python) → directory.llmstxt.cloud → npm/PyPI (trust = downloads) → GitHub search (preferensi bahasa dari query)get_docs(library_id, query)— hybrid search (BM25 + embedding bge-small-en-v1.5), cache sub-ms setelah first fetchversions(library_id)— daftar versi yang diketahui- Offline-capable: sekali di-index, cache permanen di SQLite (FTS5 + sqlite-vec)
Instalasi
uv tool install git+https://github.com/ngabzar02/memo-server
Registrasi di opencode.json (atau config MCP lain):
{
"mcp": {
"memo": {
"type": "local",
"command": ["<path ke uv tool bin>/memo"],
"enabled": true
}
}
}
Pre-index (disarankan)
Cold fetch pertama melewati batas timeout MCP (~30s) di beberapa client — panaskan cache dari shell dulu:
memo --warmup flask nextjs httpx
memo --warmup --force flask # re-ingest (docs_url berubah / force refresh)
Arsitektur
| Modul | Peran |
|---|---|
registry.py |
resolusi nama → {repo, docs_url, trust} |
ingest.py |
fetch → trafilatura → chunk 256 token (overlap 50) |
store.py |
SQLite: libs + chunks_fts (BM25) + chunks_vec (sqlite-vec) |
server.py |
FastMCP stdio server + --warmup CLI |
Data: ~/.local/share/memo/docs.db (buat sekali, dipakai semua library).
Lisensi
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.