Codeglance

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