Configuration
Configuration Guide
Configure kit-dev-mcp for your development environment
Environment Variables
LLM API Keys (Required for get_code_summary)
An LLM API key is required for the get_code_summary
tool. Choose one of:
# Option 1: OpenAI (default) export OPENAI_API_KEY="sk-..."
# Option 2: Anthropic export ANTHROPIC_API_KEY="sk-ant-..."
# Option 3: Google Gemini export GOOGLE_API_KEY="AI..."
Note: All other tools work without an LLM API key.
KIT_GITHUB_TOKEN
GitHub personal access token for accessing private repositories and increasing API rate limits.
export KIT_GITHUB_TOKEN="ghp_your_token_here"
KIT_CACHE_DIR
Directory for caching symbol extraction and documentation. Defaults to ~/.cache/kit
export KIT_CACHE_DIR="~/.cache/kit"
MCP Server Configuration
Cursor Configuration
Add to your Cursor settings.json
{ "mcpServers": { "kit-dev": { "command": "uvx", "args": ["--from", "cased-kit[all]", "kit-dev-mcp"], "env": { "OPENAI_API_KEY": "sk-...", // For get_code_summary (or use ANTHROPIC_API_KEY) "KIT_GITHUB_TOKEN": "ghp_..." // Optional: for private repos } } } }
Advanced Configuration Options
Environment Variables for Advanced Users
{ "env": { "KIT_GITHUB_TOKEN": "ghp_...", // GitHub access token "KIT_CACHE_DIR": "~/.cache/kit", // Cache directory "KIT_LOG_LEVEL": "DEBUG", // Logging level "KIT_MAX_WORKERS": "8", // Parallel workers "KIT_CACHE_TTL": "3600", // Cache TTL in seconds "KIT_DEEP_RESEARCH": "true" // Deep doc research } }
KIT_LOG_LEVEL: Set to DEBUG for verbose logging
KIT_MAX_WORKERS: Number of parallel workers (default: 4)
KIT_CACHE_TTL: Cache time-to-live in seconds
KIT_DEEP_RESEARCH: Enable deep documentation research
File Watching Configuration
Configure which files to watch and ignore:
# .kitignore file in your project root node_modules/ .git/ *.pyc __pycache__/ .venv/ dist/ build/ *.log .DS_Store
Performance Tuning
Cache Settings
- • Enable aggressive caching for large repos
- • Set appropriate TTL values
- • Use local SSD for cache directory
- • Clear cache periodically
Memory Management
- • Adjust worker count based on CPU cores
- • Limit file size for analysis
- • Configure max memory usage
- • Enable incremental processing