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.
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:
- 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 |
|---|---|
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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