MCP Repo2llm Server

@crisschan

代码仓库

基本信息

分类

其他

许可证

Apache-2.0

传输方式

stdio

作者

crisschan

提交者

Criss Chen

关于 MCP Repo2llm Server

暂无概览

#mcp-repo2llm#code-transformation#ai-integration

MCP Repo2llm 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": {
    "mcp-repo2llm-server": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "--with-editable",
        "/mcp-repo2llm",
        "mcp",
        "run",
        "/mcp-repo2llm/mcp-repo2llm-server.py"
      ],
      "env": {
        "GITHUB_TOKEN": "your-github-token",
        "GITLAB_TOKEN": "your-gitlab-token"
      }
    }
  }
}

MCP Repo2llm Server 工具

工具列表暂未提供

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。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Mcp Repo2llm Server?

Mcp Repo2llm Server is an MCP server that transforms code repositories into LLM-friendly formats, bridging the gap between traditional codebases and AI language models. It is based on the RepoToTextForLLMs project.

How to use Mcp Repo2llm Server?

Install and configure the server via uv with the required environment variables GITHUB_TOKEN and GITLAB_TOKEN. Invoke the tools get_github_repo, get_gitlab_repo, or get_local_repo with a repository URL and optional branch (default master) to receive the repository contents as formatted text.

Key features of Mcp Repo2llm Server

Smart Repository Scanning: processes entire codebases while preserving structure
Context Preservation: maintains relationships and contextual information between code files
Multi-language Support: language-specific optimizations for various programming languages
Metadata Enhancement: enriches code with relevant metadata for better LLM understanding
Efficient Processing: optimized for large repositories with minimal resource usage

Use cases of Mcp Repo2llm Server

Feed entire codebases to LLMs for analysis or code generation while retaining structural context
Convert GitLab, GitHub, or local repositories into a single text document for AI tool consumption
Standardize repository documentation and metadata for consistent LLM processing across projects
Enable AI-powered code review or refactoring by providing clean, structured repository text

常见问题

What tokens are required to use the server?

The server requires `GITHUB_TOKEN` and `GITLAB_TOKEN` environment variables to authenticate with GitHub and GitLab respectively.

Which repository hosts are supported?

The server supports GitHub (`get_github_repo`), GitLab (`get_gitlab_repo`), and local file system repositories (`get_local_repo`).

What is the default branch used when fetching a repository?

The default branch is `master` for both GitHub and GitLab tools, but you may specify a different branch via the `branch` parameter.

Does the server have any runtime dependencies?

Yes, the server requires `uv` and the `mcp[cli]` package. It is run as a Python script (`mcp-repo2llm-server.py`) based on the RepoToTextForLLMs library.

What does the output contain?

The tools return all project information and structure from the repository as a single formatted text string, suitable for input to LLMs.

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