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