Gitingest MCP Server

Gitingest MCP Server

Enables analysis and querying of Git repository content (both public and private) through a unified tool that provides repository summaries, file structures, and full content optimized for LLM consumption.

Category
访问服务器

README

Gitingest MCP server

An MCP server for gitingest that provides access to Git repository analysis through the Model Context Protocol (MCP). This server leverages the gitingest library to analyze Git repositories and make their content available in a format optimized for LLMs.

Overview

This MCP server provides a single unified tool for accessing Git repository data. It automatically handles repository ingestion as needed, so users can immediately query repository content without an explicit ingestion step.

Tool: gitingest

The server provides a single tool called gitingest that can be used to analyze Git repositories. The tool accepts the following parameters:

  • repo_uri (required): URL or local path to the Git repository
  • resource_type: Type of data to retrieve (summary, tree, content, or all). Default is summary.
  • max_file_size: Maximum file size in bytes to include in the analysis. Default is 10MB.
  • include_patterns: Comma-separated patterns of files to include in the analysis.
  • exclude_patterns: Comma-separated patterns of files to exclude from the analysis.
  • branch: Specific branch to analyze.
  • output: File path to save the output to.
  • max_tokens: Truncates the response to a specified number of tokens.

Accessing Private Repositories

You can ingest private GitHub repositories by providing a GitHub Personal Access Token (PAT).

Recommended: Set an Environment Variable in your MCP Config

This is the best approach for persistent configuration. Add an env block to your server definition in your MCP configuration file. The gitingest library will automatically use the GITHUB_TOKEN environment variable.

"mcpServers": {
  "mattdepaolis-gitingest-mcp": {
    "command": "uvx",
    "args": [
      "mattdepaolis-gitingest-mcp"
    ],
    "env": {
      "GITHUB_TOKEN": "github_pat_..."
    }
  }
}

Resource Types and Large Repositories

For large repositories, it's recommended to first request only the summary (which is the default). After ingestion, you can access more detailed information through the resources:

  • Use the tree resource to explore the repository structure
  • Use the content resource to access the full content (if not too large)

If the repository is too large, consider using include_patterns and/or exclude_patterns to limit the scope of the ingestion.

Accessing Resources After a Tool Call

After you call the gitingest tool for a repository, the server defines resources for that repository:

  • Summary: A high-level summary of the repository
  • Tree: The file/directory structure
  • Content: The full content (subject to size limits)

These resources can be accessed individually via the resources interface in any MCP-compatible client. This is useful for browsing or fetching specific aspects of a repository after ingestion.

Debugging

The best way to debug MCP servers is with the MCP Inspector.

You can launch the Inspector with your local server using this command:

npx @modelcontextprotocol/inspector uv --directory /Users/matthias/Desktop/ai_projects/MCP-Server-Gitingest/mattdepaolis-gitingest-mcp run mattdepaolis-gitingest-mcp

or using uvx for the mcp server:

npx @modelcontextprotocol/inspector uvx https://github.com/mattdepaolis/mattdepaolis-gitingest-mcp.git

or using the PyPI package:

npx @modelcontextprotocol/inspector uvx mattdepaolis-gitingest-mcp

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选