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.
🚀 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.
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.
Architecture at a glance
Pipeline
- Parse source structure (polyglot parsers)
- Extract symbols + metadata (names, signatures, byte offsets)
- Persist a lightweight local index
- Serve MCP tools for discovery
- Retrieve exact snippets via byte-offset precision
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.
Demo
Suggested demo flow:
index_repo(path=...)search_symbols(query="calculate")get_symbol("...")
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 |
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)
License
MIT