Prerequisites

Skip to content

You signed in with another tab or window. Reload
to refresh your session. You signed out in another tab or window. Reload
to refresh your session. You switched accounts on another tab or window. Reload
to refresh your session. Dismiss alert

JustTryAI / databricks-mcp-server Public

• Notifications
  You must be signed in to change notification settings

• Fork 1

• Star 6

A Model Completion Protocol (MCP) server for interacting with Databricks services

6 stars
1 fork
Branches
Tags
Activity

Star

Notifications
You must be signed in to change notification settings

JustTryAI/databricks-mcp-server

master

3 Branches
0 Tags

Go to file

Code

Folders and files

| Name | | Name | Last commit message | Last commit date |
| --- | --- | --- | --- |
| Latest commit
-------------


LBurley-Modutecture

Update README with correct repository URL and remove databricks-mcp f…

Mar 13, 2025

81cd60b
 · Mar 13, 2025

History
-------

9 Commits

| | |
| .cursor/rules | | .cursor/rules | Add Cursor rules for the Databricks MCP Server project | Mar 13, 2025 |
| docs | | docs | Move documentation from documents/ to docs/ directory | Mar 13, 2025 |
| examples | | examples | Project restructuring and cleanup: Organized code, added documentatio… | Mar 13, 2025 |
| scripts | | scripts | Add new utility scripts and server modules | Mar 13, 2025 |
| src | | src | Add new utility scripts and server modules | Mar 13, 2025 |
| tests | | tests | Update project documentation and test infrastructure | Mar 13, 2025 |
| .cursor.json | | .cursor.json | Add .cursor.json rules file for project structure and conventions | Mar 13, 2025 |
| .env.example | | .env.example | Initial commit | Mar 12, 2025 |
| .gitignore | | .gitignore | Update README with correct repository URL and remove databricks-mcp f… | Mar 13, 2025 |
| README.md | | README.md | Update README with correct repository URL and remove databricks-mcp f… | Mar 13, 2025 |
| SUMMARY.md | | SUMMARY.md | Project restructuring and cleanup: Organized code, added documentatio… | Mar 13, 2025 |
| project_structure.md | | project_structure.md | Update project documentation and test infrastructure | Mar 13, 2025 |
| pyproject.toml | | pyproject.toml | Project restructuring and cleanup: Organized code, added documentatio… | Mar 13, 2025 |
| start_mcp_server.ps1 | | start_mcp_server.ps1 | Update project documentation and test infrastructure | Mar 13, 2025 |
| start_mcp_server.sh | | start_mcp_server.sh | Standardize script organization and naming conventions | Mar 13, 2025 |
| uv.lock | | uv.lock | Project restructuring and cleanup: Organized code, added documentatio… | Mar 13, 2025 |
| View all files | | |

Repository files navigation

Databricks MCP Server

A Model Completion Protocol (MCP) server for Databricks that provides access to Databricks functionality via the MCP protocol. This allows LLM-powered tools to interact with Databricks clusters, jobs, notebooks, and more.

Features

• MCP Protocol Support: Implements the MCP protocol to allow LLMs to interact with Databricks
• Databricks API Integration: Provides access to Databricks REST API functionality
• Tool Registration: Exposes Databricks functionality as MCP tools
• Async Support: Built with asyncio for efficient operation

Available Tools

The Databricks MCP Server exposes the following tools:

• list_clusters: List all Databricks clusters
• create_cluster: Create a new Databricks cluster
• terminate_cluster: Terminate a Databricks cluster
• get_cluster: Get information about a specific Databricks cluster
• start_cluster: Start a terminated Databricks cluster
• list_jobs: List all Databricks jobs
• run_job: Run a Databricks job
• list_notebooks: List notebooks in a workspace directory
• export_notebook: Export a notebook from the workspace
• list_files: List files and directories in a DBFS path
• execute_sql: Execute a SQL statement

Installation

Prerequisites

• Python 3.10 or higher
• uv package manager (recommended for MCP servers)

Setup

1. Install uv if you don't have it already:

   ```shell

   MacOS/Linux

   curl -LsSf https://astral.sh/uv/install.sh | sh

   Windows (in PowerShell)

   irm https://astral.sh/uv/install.ps1 | iex
   ```

   Restart your terminal after installation.

2. Clone the repository:

   shell git clone https://github.com/JustTryAI/databricks-mcp-server.git cd databricks-mcp-server

3. Set up the project with uv:

   ```shell

   Create and activate virtual environment

   uv venv

   On Windows

   ..venv\Scripts\activate

   On Linux/Mac

   source .venv/bin/activate

   Install dependencies in development mode

   uv pip install -e .

   Install development dependencies

   uv pip install -e ".[dev]"
   ```

4. Set up environment variables:

   ```shell

   Windows

   set DATABRICKS_HOST=https://your-databricks-instance.azuredatabricks.net
   set DATABRICKS_TOKEN=your-personal-access-token

   Linux/Mac

   export DATABRICKS_HOST=https://your-databricks-instance.azuredatabricks.net
   export DATABRICKS_TOKEN=your-personal-access-token
   ```

   You can also create an .env file based on the .env.example template.

Running the MCP Server

To start the MCP server, run:

# Windows
.\start_mcp_server.ps1

# Linux/Mac
./start_mcp_server.sh

These wrapper scripts will execute the actual server scripts located in the scripts directory. The server will start and be ready to accept MCP protocol connections.

You can also directly run the server scripts from the scripts directory:

# Windows
.\scripts\start_mcp_server.ps1

# Linux/Mac
./scripts/start_mcp_server.sh

Querying Databricks Resources

The repository includes utility scripts to quickly view Databricks resources:

# View all clusters
uv run scripts/show_clusters.py

# View all notebooks
uv run scripts/show_notebooks.py

Project Structure

databricks-mcp-server/
├── src/                             # Source code
│   ├── __init__.py                  # Makes src a package
│   ├── __main__.py                  # Main entry point for the package
│   ├── main.py                      # Entry point for the MCP server
│   ├── api/                         # Databricks API clients
│   ├── core/                        # Core functionality
│   ├── server/                      # Server implementation
│   │   ├── databricks_mcp_server.py # Main MCP server
│   │   └── app.py                   # FastAPI app for tests
│   └── cli/                         # Command-line interface
├── tests/                           # Test directory
├── scripts/                         # Helper scripts
│   ├── start_mcp_server.ps1         # Server startup script (Windows)
│   ├── run_tests.ps1                # Test runner script
│   ├── show_clusters.py             # Script to show clusters
│   └── show_notebooks.py            # Script to show notebooks
├── examples/                        # Example usage
├── docs/                            # Documentation
└── pyproject.toml                   # Project configuration

See project_structure.md for a more detailed view of the project structure.

Development

Code Standards

• Python code follows PEP 8 style guide with a maximum line length of 100 characters
• Use 4 spaces for indentation (no tabs)
• Use double quotes for strings
• All classes, methods, and functions should have Google-style docstrings
• Type hints are required for all code except tests

Linting

The project uses the following linting tools:

# Run all linters
uv run pylint src/ tests/
uv run flake8 src/ tests/
uv run mypy src/

Testing

The project uses pytest for testing. To run the tests:

# Run all tests with our convenient script
.\scripts\run_tests.ps1

# Run with coverage report
.\scripts\run_tests.ps1 -Coverage

# Run specific tests with verbose output
.\scripts\run_tests.ps1 -Verbose -Coverage tests/test_clusters.py

You can also run the tests directly with pytest:

# Run all tests
uv run pytest tests/

# Run with coverage report
uv run pytest --cov=src tests/ --cov-report=term-missing

A minimum code coverage of 80% is the goal for the project.

Documentation

• API documentation is generated using Sphinx and can be found in the docs/api directory
• All code includes Google-style docstrings
• See the examples/ directory for usage examples

Examples

Check the examples/ directory for usage examples. To run examples:

# Run example scripts with uv
uv run examples/direct_usage.py
uv run examples/mcp_client_usage.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Ensure your code follows the project's coding standards
2. Add tests for any new functionality
3. Update documentation as necessary
4. Verify all tests pass before submitting

License

This project is licensed under the MIT License - see the LICENSE file for details.

About

A Model Completion Protocol (MCP) server for interacting with Databricks services

Resources

Readme

Activity

Stars

6 stars

Watchers

1 watching

Forks

1 fork

Report repository

Releases

No releases published

Packages 0

No packages published

Languages

• Python 82.1%

• PowerShell 13.5%

• Shell 4.4%

You can’t perform that action at this time.