Jcodemunch Mcp

by jgravelle

2k stars

847 downloads

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GitHub Website

About

Cut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.

Details

Author: jgravelle
GitHub stars: 1,990
Downloads: 847
Categories: Productivity, Other, Developer Tools

- Precise symbol retrieval (functions, classes, methods, constants)
- 95%+ token reduction in code-reading workflows
- tree-sitter based AST indexing for polyglot parsing
- Compact wire format (MUNCH) for additional token savings
- BM25 search, fuzzy matching, semantic/hybrid search (opt-in)
- Multi-repo integration, dependency indexing, dead code detection

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Jcodemunch Mcp

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

From the repository

Install via pip install jcodemunch-mcp or uvx jcodemunch-mcp. One-click install buttons are available for VS Code, VS Code Insiders, and Cursor. A quickstart guide is at QUICKSTART.md, and full documentation covers tool reference, configuration, and agent hooks.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "jcodemunch mcp": {
            "jcodemunch": {
                "command": "uvx",
                "args": [
                    "jcodemunch-mcp"
                ]
            }
        }
    }
}

McpServers

{
    "jcodemunch": {
        "command": "uvx",
        "args": [
            "jcodemunch-mcp"
        ]
    }
}

jCodeMunch MCP

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: 95% average token reduction (15 tasks / 3 repos, 99.8% peak).

Works with Claude Code, Cursor, VS Code, Codex CLI, Continue, Windsurf, and any MCP-compatible client.

---

One-click installs:

Prefer the command line?

pip install jcodemunch-mcp
uvx jcodemunch-mcp

For pinned/B2B deployments that want a version-stable install channel independent of PyPI, install straight from the repo (requires git, builds from source):

pip install git+https://github.com/jgravelle/jcodemunch-mcp.git
uvx --from git+https://github.com/jgravelle/jcodemunch-mcp.git jcodemunch-mcp

Quickstart - https://github.com/jgravelle/jcodemunch-mcp/blob/main/QUICKSTART.md

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/

FREE FOR PERSONAL USE

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!

---

Cut code-reading token usage by 95% or more with precise symbol retrieval

Most AI agents explore repositories the expensive way:

open entire files → skim thousands of irrelevant lines → repeat.

That is not “a little inefficient.”
That is a token incinerator.

jCodeMunch indexes a codebase once and lets agents retrieve only the exact code they need: functions, classes, methods, constants, outlines, and tightly scoped context bundles, with byte-level precision.

In retrieval-heavy workflows, that routinely cuts code-reading token usage by 95%+ because the agent stops brute-reading giant files just to find one useful implementation.

| Task | Traditional approach | With jCodeMunch |
| ---------------------- | ------------------------- | ------------------------------------------- |
| Find a function | Open and scan large files | Search symbol → fetch exact implementation |
| Understand a module | Read broad file regions | Pull only relevant symbols and imports |
| Explore repo structure | Traverse file after file | Query outlines, trees, and targeted bundles |

Index once. Query cheaply. Keep moving.
Precision context beats brute-force context.

---

Documentation

| Doc | What it covers |
|-----|----------------|
| QUICKSTART.md | Zero-to-indexed in three steps |
| USER_GUIDE.md | Full tool reference, workflows, and best practices |
| AGENT_HOOKS.md | Agent hooks and prompt policies |
| CONFIGURATION.md | JSONC config file reference, migration from env vars |
| GROQ.md | Groq Remote MCP integration, deployment, gcm CLI |
| HEADLESS.md | Using jCodeMunch with claude -p (and the jragmunch CLI) |
| ARCHITECTURE.md | Internal design, storage model, and extension points |
| LANGUAGE_SUPPORT.md | Supported languages and parsing details |
| CONTEXT_PROVIDERS.md | dbt, Git, and custom context provider docs |
| TROUBLESHOOTING.md | Common issues and fixes |
| AGENT_INSTALL_UNIVERSAL.md | Paste-and-go prompt for installing jCodemunch guidance into agent/IDE clients without a first-class jcm install target (Codex CLI, Cline, JetBrains AI, Aider, etc.). For Claude Code, Cursor, Windsurf, Continue — use jcm install <client> instead. |

---

Compact output — the second token axis (MUNCH)

Retrieval decides what to send. MUNCH decides how to pack it.

Every tool response can be emitted in a purpose-built compact wire format
instead of verbose JSON. Path prefixes are interned to short handles,
homogeneous lists of dicts pack into single-character-tagged CSV rows, and
per-column types are preserved so the decode is lossless.

```python

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

jCodeMunch MCP

One-click installs:

FREE FOR PERSONAL USE

Cut code-reading token usage by 95% or more with precise symbol retrieval

Documentation

Compact output — the second token axis (MUNCH)

Install

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