jCodeMunch MCP

Make AI agents cheaper and faster on real codebases

Stop dumping files into context windows. Start retrieving exactly what the agent needs.

jCodeMunch MCP indexes a local codebase once, then lets MCP-compatible agents (Claude Desktop, OpenClaw, etc.) discover and retrieve code by symbol instead of brute-reading files.

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🚀 Proof first: Token savings in the wild

Repo: geekcomputers/Python
Size: 338 files • 1422 symbols indexed
Task: Find calculator/math implementations

Approach	Tokens (this run)	What the agent had to do
Raw file approach	~7,500	Open multiple files blindly and skim
jCodeMunch MCP	~1,449	search_symbols(...) → get_symbol(...)

Result: 80.7% fewer tokens (≈5.2× more efficient)

Cost scales with tokens. Latency often scales with “how much junk the model must read”.
jCodeMunch reduces both by turning search into navigation.

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Why agents need this (and humans benefit too)

Agents waste money when they:

• open entire files just to find one function
• re-read the same code repeatedly
• drown in imports, boilerplate, and unrelated helpers

jCodeMunch gives agents structured access:

• Search symbols by name/topic
• Outline files without loading full contents
• Retrieve only the exact implementation of a symbol

Agents don’t need more context. They need precision context access.

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Architecture at a glance

Pipeline

1. Parse source structure (polyglot parsers)
2. Extract symbols + metadata (names, signatures, byte offsets)
3. Persist a lightweight local index
4. Serve MCP tools for discovery
5. Retrieve exact snippets via byte-offset precision

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Quickstart

git clone https://github.com/jgravelle/jcodemunch-mcp
cd jcodemunch-mcp
pip install -r requirements.txt

Configure your MCP client (Claude Desktop / OpenClaw)

Point the server at any local folder containing a codebase. Index once, then query.

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Demo

Suggested demo flow:

1. index_repo(path=...)
2. search_symbols(query="calculate")
3. get_symbol("...")

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Tool suite

Tool	Purpose
index_repo	Index any local codebase folder
search_symbols	Find symbols by name/topic
get_file_outline	View a file’s structural “API skeleton”
get_symbol	Retrieve the exact implementation

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What it’s great for

• Large, messy repos where grepping is painful
• Agentic refactors across many files
• “Where is X implemented?” or “Who calls Y?” exploration
• Fast onboarding and architecture discovery
• Running cheaper agent swarms (OpenClaw-style)

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License

MIT