jgravelle/jcodemunch-mcp
Symbol-level code retrieval for AI agents: fetch the function you need, not the whole file. Runs locally. 96.2% fewer tokens per lookup than grep-and-read on our 15-lookup benchmark. Works with Claude Code, Cursor, Codex and any MCP client.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 2 days ago, with 57 contributors on GitHub.
Use Cases & Benefits
- Provides a token-efficient MCP server for precise symbol-level GitHub code retrieval using tree-sitter AST parsing to reduce AI token costs during code exploration.
- Significantly lowers AI token usage by over 95% through structured retrieval of exact code symbols instead of reading entire files, optimizing context window usage.
- Use for integrating with AI coding assistants like Claude Code or Cursor to enable fast, precise code lookups and reduce token consumption in large repositories.
- Ideal for developers needing detailed codebase analysis such as dead code detection, call hierarchy tracing, and architectural ranking without language server overhead.
- Use for automating risk assessment and refactoring plans by leveraging features like blast radius scoring, change impact analysis, and edit safety verification.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Other
GitHub could not identify this license; read the LICENSE file before depending on it.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
- License not identified by GitHub; read the LICENSE file before depending on it.
General guidance from repository metadata, not legal advice. How we score
From the README
The leading, most token-efficient MCP server for precise GitHub source code retrieval via tree-sitter AST parsing. Cut AI token costs 95%+ on code exploration — stop burning your context window reading entire files.
Real results, live from production 335B+ tokens saved · 48,000+ developers · $1.69M+ in AI spend avoided · 40,000+ kg CO₂ prevented Live telemetry at jcodemunch.com — benchmark: 99.6% average token reduction (15 tasks / 3 repos, 99.9% peak; run 2026-07-23).
Works with Autohand Code, Claude Code, Cursor, VS Code, Codex CLI, Continue, Windsurf, and any MCP-compatible client.
Prefer the command line?
For pinned/B2B deployments that want a version-stable install channel independent of PyPI, install straight from the repo (requires
git, builds from source):A crapload of detailed info: http://jcodemunch.com/
Live OSS code-health observatory — weekly six-axis health snapshots of Express, FastAPI, Gin, Pydantic, Django, Flask, NestJS, Cobra, and this very repo: https://jgravelle.github.io/jcodemunch-observatory/
Token Cost Radar — daily intelligence on AI token costs, minimization strategies, and budget trends for teams running Claude Code / Cursor / MCP: https://jcodemunch.com/radar/
Use it to make money, and Uncle J. gets a taste. Fair enough? details
Our guarantee: If jCodeMunch doesn't pay for itself, you don't pay for jCodeMunch!
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
371+38
Open issues
26+21
Compared with peers in Developer Tools
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| stablyai/orca | 116.8K | +6.6K | 40 | today |
| affaan-m/ECC | 297.9K | +5.2K | 63 | 35 days ago |
| DietrichGebert/ponytail | 185.3K | +5.1K | 60 | 7 days ago |
| herdrdev/herdr | 48.3K | +1.7K | 59 | 22 days ago |
| The-PR-Agent/pr-agent | 15.1K | +1.5K | 64 | 11 days ago |
| jgravelle/jcodemunch-mcp | 2.8K | — | 65 | 2 days ago |
| Category median | 116.8K | +5.1K | 60 | — |
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