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Jcodemunch MCP Server

@jgravelle

基本信息

分类

其他

许可证

NOASSERTION

传输方式

stdio

作者

jgravelle

提交者

J. Gravelle

关于 Jcodemunch MCP Server

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.

Jcodemunch MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Jcodemunch MCP Server 工具

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当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Jcodemunch Mcp?

Jcodemunch Mcp is a token-efficient MCP server for precise GitHub source code retrieval via tree-sitter AST parsing. It cuts AI token costs by 95%+ by indexing codebases once and retrieving only exact symbols (functions, classes, methods) instead of entire files. It is designed for developers using AI agents like Claude Code, Cursor, VS Code, and any MCP-compatible client.

How to use Jcodemunch Mcp?

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.

Key features of Jcodemunch Mcp

  • 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

Use cases of Jcodemunch Mcp

  • Finding a function implementation without scanning entire files
  • Understanding module structure via outlines and targeted bundles
  • Exploring repo structure with query-driven context retrieval
  • Reducing AI token spend in retrieval-heavy workflows
  • Analyzing code health with observatory tools (e.g., six-axis health snapshots)

常见问题

1

What does Jcodemunch Mcp do differently than reading entire files?

It indexes the codebase using tree-sitter and retrieves only the exact code needed (symbols, outlines, context bundles) with byte-level precision, cutting token usage by 95%+.

2

What are the runtime requirements?

Jcodemunch Mcp requires Python and can be installed via pip or uvx. It runs locally and works with any MCP-compatible client (Claude Code, Cursor, VS Code, etc.).

3

Where does the data live?

Indexes are stored locally on the user's machine. The server is local-first; no external data transfer is required.

4

What transports and authentication does it use?

It uses the standard MCP protocol (stdio transport by default). No authentication mechanism is specified in the README.

5

Is Jcodemunch Mcp free for commercial use?

No, it is free for non-commercial use only. Commercial use requires a paid license: Builder ($79/1 dev), Studio ($349/up to 5 devs), or Platform ($1,999/org-wide).

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