jDocmunch MCP
Section-level doc search for .md, .rst, .adoc, .ipynb, .html, .yaml, .json, and OpenAPI specs.
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<!-- mcp-name: io.github.jgravelle/jdocmunch-mcp --> ## Stop Feeding Documentation Trees to Your AI Most AI agents still explore documentation the expensive way: open file → skim hundreds of irrelevant paragraphs → open another file → repeat That burns tokens, floods context windows with noise, and forces models to reason through a lot of text they never needed in the first place. **jDocMunch-MCP lets AI agents navigate documentation by section instead of reading files by brute force.** It indexes a documentation set once, then retrieves exactly the section the agent actually needs, with byte-precise extraction from the original file. | Task | Traditional approach | With jDocMunch | | --- | ---: | ---: | | Find a configuration section | ~12,000 tokens | ~400 tokens | | Browse documentation structure | ~40,000 tokens | ~800 tokens | | Explore a full doc set | ~100,000 tokens | ~2,000 tokens | Index once. Query cheaply forever. **Precision context beats brute-force context.** --- # jDocMunch MCP ### AI-native documentation navigation for serious agents     [](https://pypi.org/project/jdocmunch-mcp/) [](https://pypi.org/project/jdocmunch-mcp/) > ## Commercial licenses > jDocMunch-MCP is **free for non-commercial use**. > > **Commercial use requires a paid license.** > > **jDocMunch-only licenses** > - [Builder — $29](https://j.gravelle.us/jCodeMunch/descriptions.php#builder) — 1 developer > - [Studio — $99](https://j.gravelle.us/jCodeMunch/descriptions.php#studio) — up to 5 developers > - [Platform — $499](https://j.gravelle.us/jCodeMunch/descriptions.php#platform) — org-wide internal deployment > > **Want both code and docs retrieval?** > - [Munch Duo Builder Bundle — $89](https://j.gravelle.us/jCodeMunch/descriptions.php#builder) > - [Munch Duo Studio Bundle — $399](https://j.gravelle.us/jCodeMunch/descriptions.php#studio) > - [Munch Duo Platform Bundle — $2,249](https://j.gravelle.us/jCodeMunch/descriptions.php#platform) **Stop dumping documentation files into context windows. Start navigating docs structurally.** jDocMunch indexes documentation once by heading hierarchy and section structure, then gives MCP-compatible agents precise access to the explanations they actually need instead of forcing them to brute-read files. It is built for workflows where token efficiency, context hygiene, and agent reliability matter. --- ## Why this exists Large context windows do not fix bad retrieval. Agents waste money and reasoning bandwidth when they: - open entire documents to find one configuration block - repeatedly re-read headings, boilerplate, and unrelated sections - lose important explanations inside oversized context payloads - consume documentation as flat text instead of structured knowledge jDocMunch fixes that by changing the unit of access from **file** to **section**. Instead of handing an agent an entire document, it can retrieve exactly: - an installation section - a configuration section - an API explanation - a troubleshooting section - a specific subtree of related headings That makes documentation exploration cheaper, faster, and more stable. --- ## What makes it different ### Section-first retrieval Search and retrieve documentation by section, not just file path or keyword match. ### Byte-precise extraction Full content is pulled on demand from exact byte offsets into the original file. ### Stable section IDs Sections retain durable identities across re-indexing when path, heading text, and heading level remain unchanged. ### Local-first architecture Indexes and raw docs are stored locally. No hosted dependency required. ### MCP-native workflow Works with Claude Desktop, Claude Code, Google Antigravity, and other MCP-compatible clients. --- ## What gets indexed Every section stores: - title and heading level - one-line summary - extracted tags and references - SHA-256 content hash for drift detection - byte offsets into the original file This allows agents to discover documentation structurally, then request only the specific section they need. --- ## Why agents need this Traditional doc retrieval methods all break in different ways: - **File scanning** loads far too much irrelevant text - **Keyword search** finds terms but often loses context - **Chunking** breaks authored hierarchy and separates explanations from examples jDocMunch preserves the structure the human author intended: - heading hierarchy - parent/child relationships - section boundaries - coherent explanatory units Agents do not need bigger context windows. They need better navigation. --- ## How