codeglance-mcp

codeglance-mcp

Analyzes GitHub repositories using Gemini AI and generates comprehensive documentation including overviews, architecture guides, and file insights. Works with any MCP-compatible client.

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README

CodeGlance MCP Server

An MCP (Model Context Protocol) server that analyzes GitHub repositories using Gemini AI and generates comprehensive documentation — project overviews, architecture guides, file insights, and more.

Works with any MCP-compatible client: Claude Code, Claude Desktop, Cursor, Windsurf, etc.

Quick Start

1. Get a Gemini API Key

Get a free API key from Google AI Studio.

2. Install & Configure

Claude Code

claude mcp add codeglance -e GEMINI_API_KEY=your_key_here -- uvx codeglance-mcp

That's it. Verify with:

claude mcp list

Claude Desktop / Cursor / Other MCP Clients

Add to your MCP config file (claude_desktop_config.json, .cursor/mcp.json, etc.):

{
  "mcpServers": {
    "codeglance": {
      "command": "uvx",
      "args": ["codeglance-mcp"],
      "env": {
        "GEMINI_API_KEY": "your_gemini_api_key_here"
      }
    }
  }
}

Alternative: Install via pip

pip install codeglance-mcp

Then configure your MCP client to run codeglance-mcp as the command instead of uvx codeglance-mcp.

What It Does

When you ask your AI assistant to analyze a repository, CodeGlance:

  1. Clones the repository (shallow clone for speed)
  2. Reads key files (README, package.json, config files, entry points)
  3. Sends the context to Gemini AI with specialized analysis prompts
  4. Generates 6 documentation files in codeglance-analysis/guide/

Generated Documentation

File Description
01-overview.md 5-minute project overview
02-tree.md Annotated directory structure
03-file-insights.md Key files and their purposes
04-architecture.md System architecture deep-dive
05-quick-start.md Getting started guide
06-master-analysis.md Comprehensive technical analysis

MCP Tools

Tool Description
analyze_repository Run full analysis on a GitHub repo
get_repository_info Check if a repo is already cloned
list_generated_guides List generated documentation files

MCP Prompts

Prompt Description
comprehensive_analysis Full analysis workflow
quick_overview Fast overview only
architecture_review Architecture-focused analysis
security_audit Security-focused review

Configuration

All settings can be customized via environment variables in your MCP config:

Variable Default Description
GEMINI_API_KEY (required) Your Google Gemini API key
MAX_FILE_SIZE 5000 Max characters per file to analyze
MAX_FILES_PER_ANALYSIS 50 Max files to include in analysis
TIMEOUT_SECONDS 120 API request timeout
MAX_CONCURRENT_REQUESTS 3 Concurrent Gemini API calls
CACHE_TTL_SECONDS 3600 In-memory cache TTL

Example with custom settings:

{
  "mcpServers": {
    "codeglance": {
      "command": "uvx",
      "args": ["codeglance-mcp"],
      "env": {
        "GEMINI_API_KEY": "your_key",
        "TIMEOUT_SECONDS": "180",
        "MAX_CONCURRENT_REQUESTS": "5"
      }
    }
  }
}

Requirements

  • Python 3.11+
  • Git (for cloning repositories)
  • A Gemini API key (free tier works)

Development

git clone https://github.com/lucidopus/codeglance-mcp.git
cd codeglance-mcp
uv sync

# Run locally
GEMINI_API_KEY=your_key uv run codeglance-mcp

License

MIT

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