# Install from PyPI
pip install mlops-mcp-server

# Or install with all optional dependencies
pip install mlops-mcp-server[all]

{
  "mcpServers": {
    "mlops": {
      "command": "mlops-mcp-server",
      "env": {
        "MLFLOW_TRACKING_URI": "http://localhost:5000"
      }
    }
  }
}

User: Show me all my MLflow experiments

Claude: [Uses mlflow_list_experiments]
Found 5 experiments:
1. fraud-detection (ID: 1) - 23 runs
2. recommendation-engine (ID: 2) - 45 runs
...

User: Which model has the highest accuracy in the fraud-detection experiment?

Claude: [Uses mlflow_get_best_run]
Best run: run_abc123
- Accuracy: 0.956
- Model: XGBoost
- Parameters: max_depth=6, learning_rate=0.1

User: Compare the last 3 runs in terms of accuracy and F1 score

Claude: [Uses mlflow_compare_runs]
| Run ID | Accuracy | F1 Score |
|--------|----------|----------|
| abc123 | 0.956    | 0.943    |
| def456 | 0.948    | 0.935    |
| ghi789 | 0.951    | 0.940    |

# Clone the repository
git clone https://github.com/elliottdevo8/mlops-mcp-server.git
cd mlops-mcp-server

# Create virtual environment
python -m venv venv
source venv/bin/activate

# Install in development mode
pip install -e ".[dev]"

pytest tests/ -v

# Start the server
python -m mlops_mcp.server

# Or use the CLI entry point
mlops-mcp-server