What is Mcp Repo2llm

mcp-repo2llm is an MCP server that transforms code repositories into formats compatible with Large Language Models (LLMs), facilitating better interaction between traditional codebases and modern AI tools.

Use cases

Use cases include transforming large codebases for AI-assisted development, improving code documentation for LLM understanding, and enhancing code analysis tools with enriched metadata.

How to use

To use mcp-repo2llm, install it via the command line using the provided installation instructions, and run the server to start processing code repositories into LLM-friendly formats.

Key features

Key features include smart repository scanning, context preservation, multi-language support, metadata enhancement, and efficient processing for large repositories.

Where to use

mcp-repo2llm can be used in software development environments where AI and LLMs are employed for code analysis, generation, and documentation.

MCP-Repo2LLM

Overview

mcp-repo2llm is a MCP server that transforms code repositories into LLM-friendly formats.
A powerful tool that transforms code repositories into LLM-friendly formats, bridging the gap between traditional code bases and modern AI language models.
This repo is based on RepoToTextForLLMs, which provides core functionality for converting repositories into LLM-readable formats.

Motivation

As AI and Large Language Models (LLMs) become increasingly important in software development, there’s a growing need to effectively communicate our codebases to these models. Traditional code repositories aren’t optimized for LLM processing, which can lead to suboptimal results when using AI tools for code analysis and generation.

Problem Solved

This project addresses several critical challenges:

• Difficulty in processing large codebases with LLMs
• Loss of context and structure when feeding code to AI models
• Inefficient handling of repository metadata and documentation
• Inconsistent formatting across different programming languages

Key Features

• Smart Repository Scanning: Intelligently processes entire codebases while maintaining structural integrity
• Context Preservation: Maintains important contextual information and relationships between code files
• Multi-language Support: Handles various programming languages with language-specific optimizations
• Metadata Enhancement: Enriches code with relevant metadata for better LLM understanding
• Efficient Processing: Optimized for handling large repositories with minimal resource usage

Installation

To install mcp-repo2llm by uv:

"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"
      }
    }

GITHUB_TOKEN: your github token
GITLAB_TOKEN: your gitlab token

Tools

get_gitlab_repo

• Process and return the code from a GitLab repository branch as text
• Input:
  • repo_url (string): the repository URL from gitlab
  • branch (string): The branch name,default is master
• Returns(string): The project all information and struction from the repository as text

get_github_repo

• Process and return the code from a Github repository branch as text
• Input:
  • repo_url (string): the repository URL from github
  • branch (string): The branch name,default is master
• Returns(string): The project all information and struction from the repository as text

get_local_repo

• Process and return the code from a GitLab repository branch as text
• Input:
  • repo_url (string): the repository path
• Returns(string): The project all information and struction from the repository as text