gnosis-mcp

MCP.Pizza Chef: nicholasglazer

Gnosis MCP is a local server that lets your AI assistant search through your own documentation quickly and privately. It works with apps like Claude Desktop, VS Code, and Cursor by indexing your docs into a fast searchable database. You install it using pip, Docker, or uvx, then ingest your docs once. After that, your AI can find precise answers from markdown, text, notebooks, and more, without sending data to the cloud or needing API keys. Setup requires some developer steps but no complex configuration.

Files/PDF
Other
Web/Research

Use This MCP server To

Search my local documentation instantly Find exact answers in multiple doc files Save tokens by retrieving short relevant excerpts Ingest and search git commit messages Crawl and index documentation websites Use semantic search without an API key Keep all my docs private on my own machine

README

Gnosis MCP

Stop pasting files into context. Your AI agent searches your local docs instead.
5–10× fewer tokens per lookup. 92 % Hit@5 on real dev docs. Zero cloud dependencies.

PyPI Downloads Python MIT License CI

Quick Start · Git History · Web Crawl · Backends · Editors · Tools · Embeddings · Full Reference

Gnosis MCP — ingest docs, search, view stats, serve
Ingest docs → Search with highlights → Stats overview → Serve to AI agents


Without a docs server

  • LLMs hallucinate API signatures that don't exist
  • Entire files dumped into context — 3,000–15,000 tokens per doc
  • Architecture decisions buried across dozens of files
  • Every repeated lookup pays full context cost

With Gnosis MCP

  • search_docs returns ranked, highlighted excerpts — typically 300–800 tokens
  • Real answers grounded in your actual docs, not guesses from training data
  • One local index across hundreds of files — instant multi-doc search
  • 5–10× token savings per lookup when your corpus covers the question

What makes gnosis-mcp different

  • Your data stays on your machine. SQLite by default, PostgreSQL at scale — nothing leaves the host.
  • Index anything that's docs-shaped. Markdown, git commit history, crawled websites — one index, one search API.
  • Measured, not marketed. Ships BEIR SciFact numbers (0.671 nDCG@10 — within 1 % of the Lucene BM25 baseline), a reproducible eval harness (gnosis-mcp eval), and a chunk-size sweep showing where the quality plateau actually sits.

gnosis-mcp FAQ

Can I use this to search my local documentation quickly?
Yes — gnosis-mcp lets your AI search and find answers in your own docs without uploading data anywhere.
Can I use gnosis-mcp with Claude Desktop or VS Code?
Yes — it supports Claude Desktop, Cursor, VS Code, Cline, and Windsurf clients.
Do I need an API key or account to use gnosis-mcp?
No — it runs locally with zero cloud dependencies and no API keys required.
How hard is it to set up gnosis-mcp?
It requires developer-level setup, including installing via pip, Docker, or uvx, and running commands to ingest and serve your docs.
Can gnosis-mcp handle different document formats?
Yes — it supports markdown, text, notebooks, toml, csv, json, and optionally pdf and rst files.
Does gnosis-mcp keep my data private?
Yes — all your data stays on your machine; nothing is sent to the cloud.
Can I update my docs after setup?
Yes — it has watch mode to auto-re-ingest changed files and commands to prune deleted docs.