jdocmunch-mcp MCP Server
jgravelle/jdocmunch-mcp
[](https://agentrank-ai.com/tool/jgravelle--jdocmunch-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) The leading, most token-efficient MCP server for documentation exploration and retrieval via structured section indexing
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
jgravelle/jdocmunch-mcp is a Python MCP server. The leading, most token-efficient MCP server for documentation exploration and retrieval via structured section indexing Topics: claude, claude-code, docs, documentation, llm, markdown, mcp, mcp-server, codex, copilot, cursor, documentation-tool, gemini-cli, model-context-protocol, openapi, semantic-search, technical-writing, token-optimization, wiki, windsurf.
Ranked #706 out of 24846 indexed tools.
In the top 3% of all indexed tools.
Ecosystem
Score Breakdown
204 stars → growing community
Last commit 29d ago → recently updated
119/119 issues closed → responsive maintainer
7 contributors → small team
No dependents → no downstream usage
2,093 weekly installs → gaining traction
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
# jDocMunch MCP **jDocMunch is an MCP server for coding agents that retrieves the exact documentation section a task needs, without loading whole files into the context window.** Index a documentation set once by heading hierarchy, then fetch a single section, a heading subtree, or a ranked search result — extracted byte-precisely from the original file. [**Install**](#install) · [**Quickstart**](#quickstart) · [**Benchmarks**](benchmarks/) · [**Commercial licensing**](#licensing-and-commercial-use) **Free for personal use.** Commercial use requires a paid license — [terms below](#licensing-and-commercial-use). --- ## Why jDocMunch? **The problem.** An agent asked "how do I configure authentication?" opens a documentation file, skims hundreds of paragraphs it does not need, opens another, and repeats. Large context windows do not fix this. They just make the waste affordable enough to ignore until the bill arrives, and they crowd out the context the model actually needed. **TheRead full README on GitHub →
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