Gnosis Mcp

Name: Gnosis Mcp
Author: nicholasglazer

@nicholasglazer

リポジトリホームページ

Gnosis Mcp について

Zero-config MCP server for searchable documentation (SQLite default, PostgreSQL optional)

基本情報

カテゴリ

その他

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

nicholasglazer

投稿者

Nicholas

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "gnosis": {
      "command": "gnosis-mcp",
      "args": [
        "serve"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Gnosis MCP?

Gnosis MCP is a Model Context Protocol server that lets AI coding assistants search your local documentation instead of pasting entire files into context. It indexes local files, git commit history, and crawled websites into a local database, then provides ranked, highlighted snippets via search_docs — typically 300–800 tokens per lookup. It is designed for developers using AI agents who want to reduce token usage (5–10× fewer tokens per lookup) and keep data local (SQLite by default, no cloud dependencies).

How to use Gnosis MCP?

Install via pip install gnosis-mcp, then run gnosis-mcp ingest ./docs/ to load documents into SQLite and gnosis-mcp serve to start the MCP server. Connect your editor (Claude Code, Cursor, Windsurf, VS Code, JetBrains, Cline) by adding the server configuration (e.g., "command": "gnosis-mcp", "args": ["serve"]). Optional extras include gnosis-mcp[embeddings] for hybrid semantic+keyword search and gnosis-mcp[web] for crawling websites. To run with Docker, use docker run -p 8000:8000 -v "$PWD/docs:/docs:ro" -v gnosis-data:/data ghcr.io/nicholasglazer/gnosis-mcp:latest.

Key features of Gnosis MCP

Zero‑config setup with SQLite by default (pip install and go)
Hybrid search combining BM25 keyword + local ONNX embeddings (no API key)
Cross‑encoder reranking optional (off by default; test before enabling)
Ingest git commit history as searchable context (ingest-git)
Web crawl from any website via sitemap or link crawl (crawl)
Multi‑format support: .md, .txt, .ipynb, .toml, .csv, .json, .rst, .pdf
Auto‑linking via relates_to frontmatter for navigable document graph
Watch mode, prune (delete stale chunks), and wipe for full re‑ingest
Built‑in eval harness (gnosis-mcp eval) for Hit@K, MRR, Precision@K
PostgreSQL backend (pgvector + tsvector) ready for larger scale
REST API alongside MCP on the same port (v0.10.0+)