Turn Any GitHub Repository into Context for Your AI Assistant

Stop copying and pasting code snippets into your AI conversations. With mcp-git-ingest, your AI assistant can directly analyze any GitHub repository's structure and read its important files in seconds.

Why You Need Repository Context in Your AI Workflow

You're already using AI assistants for code review, debugging, and architecture discussions. But you're probably still manually feeding them context—copying README files, pasting code snippets, describing project structures. That's time you could spend actually building.

mcp-git-ingest eliminates this friction by giving your AI assistant direct access to GitHub repositories. Point it at any repo URL and instantly get:

• Complete directory trees with clean, readable formatting
• Important file contents (README, package.json, requirements.txt, etc.)
• Smart caching that avoids repeated clones
• Error handling that actually works in real-world scenarios

What This Looks Like in Practice

Instead of this painful workflow:

# Clone repo locally
git clone https://github.com/someone/interesting-project
cd interesting-project
# Copy README contents to AI chat
# Manually describe project structure
# Paste specific files when asked

You get this:

$ llm "analyze https://github.com/someone/interesting-project architecture"
# AI automatically fetches repo structure and key files
# Provides architectural analysis in seconds

Real Use Cases That Save Hours

Code Review Prep: Before diving into a new codebase, get your AI to map out the architecture, identify key entry points, and spot potential issues.

Dependency Analysis: Quickly understand what a project depends on and how it's structured without cloning locally.

Open Source Evaluation: Rapidly assess libraries and tools by having your AI analyze their code organization and documentation quality.

Onboarding: Help new team members understand codebases by generating architectural overviews and component explanations.

Documentation: Create better docs by having AI analyze your own repos and suggest improvements based on actual code structure.

Technical Implementation That Actually Works

Built with fastmcp and gitpython, mcp-git-ingest handles the messy parts of repository analysis:

• Deterministic temp directories based on repo URL hashes
• Automatic cleanup that prevents disk bloat
• Smart error handling for network issues and missing files
• Unicode tree rendering that's actually readable

The caching system means repeated requests to the same repo are fast, while the cleanup ensures you won't fill up your disk with temporary clones.

Setup in 2 Minutes

Add to your MCP configuration:

{
    "mcpServers": {
        "mcp-git-ingest": {
            "command": "uvx",
            "args": ["--from", "git+https://github.com/adhikasp/mcp-git-ingest", "mcp-git-ingest"]
        }
    }
}

That's it. Your AI assistant now has GitHub repository superpowers.

Why This Matters for Your Workflow

The real value isn't just convenience—it's about having better conversations with your AI assistant. When your AI has full context about a repository's structure and important files, it can:

• Give more accurate architectural advice
• Suggest better refactoring approaches
• Identify patterns and potential issues
• Provide more relevant code examples
• Help with more complex debugging scenarios

You're not just saving time on manual copy-paste. You're unlocking deeper, more productive AI interactions that actually understand your codebase.