codeglance-mcp
Analyzes GitHub repositories by cloning and reading key files to generate documentation.
Uses Gemini AI to perform analysis and generate comprehensive documentation from repository content.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@codeglance-mcpAnalyze the GitHub repo https://github.com/tiangolo/fastapi"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-mcpThat's it. Verify with:
claude mcp listClaude 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-mcpThen 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:
Clones the repository (shallow clone for speed)
Reads key files (README, package.json, config files, entry points)
Sends the context to Gemini AI with specialized analysis prompts
Generates 6 documentation files in
codeglance-analysis/guide/
Generated Documentation
File | Description |
| 5-minute project overview |
| Annotated directory structure |
| Key files and their purposes |
| System architecture deep-dive |
| Getting started guide |
| Comprehensive technical analysis |
MCP Tools
Tool | Description |
| Run full analysis on a GitHub repo |
| Check if a repo is already cloned |
| List generated documentation files |
MCP Prompts
Prompt | Description |
| Full analysis workflow |
| Fast overview only |
| Architecture-focused analysis |
| Security-focused review |
Configuration
All settings can be customized via environment variables in your MCP config:
Variable | Default | Description |
| (required) | Your Google Gemini API key |
|
| Max characters per file to analyze |
|
| Max files to include in analysis |
|
| API request timeout |
|
| Concurrent Gemini API calls |
|
| 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-mcpLicense
MIT
Resources
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