A command-line interface for Dagster+, inspired by GitHub's gh
CLI.
# Install with uv (recommended - adds 'dgc' to PATH)
uv tool install dagster-cli
# Or install with pip
pip install dagster-cli
# Authenticate with your Dagster+ deployment
dgc auth login
# Check health status of all assets (find problems)
dgc asset health
# View details about a specific asset
dgc asset view analytics/daily_revenue
# View logs for a failed run (see stack traces)
dgc run logs abc123 --stderr
# List recent runs to find failures
dgc run list --limit 10
Note: All commands support --help
for detailed options and --tldr
for quick examples.
Run the MCP server without installation using uvx:
# Start MCP server for Claude Code integration
uvx --from dagster-cli dgc mcp start
Configure Claude Code by adding to your MCP settings:
{
"mcpServers": {
"dagster-cli": {
"command": "uvx",
"args": ["--from", "dagster-cli", "dgc", "mcp", "start"]
}
}
}
This enables AI assistants to:
- Check asset health and identify failures
- Investigate failed runs and view error logs
- Monitor job execution and debug issues
- Access stderr/stdout logs for troubleshooting
# List all deployments including branches
dgc deployment list
# Get filtered logs from a branch deployment (e.g., for PR review)
dgc run list --deployment feat-new-feature --status FAILURE --limit 5
dgc run logs abc123 --deployment feat-new-feature --stderr
# Filter runs by job name on a specific deployment
dgc run list --deployment staging --job daily_etl --limit 10
- Secure Authentication - Store credentials safely with profile support
- Job Management - List, view, and run Dagster jobs from the terminal
- Run Monitoring - Track run status, view logs, and analyze failures
- Asset Management - List, materialize, and monitor asset health
- Repository Operations - List and reload code locations
- Profile Support - Manage multiple Dagster+ deployments
- Branch Deployment Support - Access branch deployments for testing and debugging
- Deployment Discovery - List and test available deployments
- MCP Integration - AI assistant integration for monitoring and debugging
dgc auth login # Set up credentials
dgc auth status # View current profile
dgc auth switch staging # Switch between profiles
dgc auth login --profile staging # Create new profile
dgc job list --profile production # Use specific profile
DAGSTER_CLOUD_TOKEN
- User tokenDAGSTER_CLOUD_URL
- Deployment URLDGC_PROFILE
- Default profileDAGSTER_CLOUD_DEPLOYMENT
- Default deployment
Credentials stored in ~/.config/dagster-cli/config.json
# Run tests
uv run pytest
# Format and lint
make fix
# Build package
uv build