MCP Server for Databricks
The MCP Server for Databricks allows large language models to run SQL queries, list jobs, and check job statuses directly through a secure server interface, facilitating seamless management and data analysis.
Added on:
Created by:
Apr 24 2025
The MCP Server for Databricks allows large language models to run SQL queries, list jobs, and check job statuses directly through a secure server interface, facilitating seamless management and data analysis.
Added on:
Created by:
Apr 24 2025
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What is MCP Server for Databricks?
This MCP server integrates with Databricks API, providing essential functionalities such as executing SQL queries on Databricks SQL warehouses, listing all available jobs, obtaining specific job statuses, and retrieving detailed job information. It is designed for users needing programmatic control and natural language interaction with their Databricks environment, enabling efficient data manipulation, job management, and monitoring. The server supports easy setup, including credential configuration and connection testing, making it suitable for data engineers, data scientists, and developers looking to streamline their workflows with automation and MCP protocol support.
Who will use MCP Server for Databricks?
- Data Engineers
- Data Scientists
- Developers
- ML Engineers
- Data Analysts
How to use the MCP Server for Databricks?
- Step 1: Clone the MCP server repository from GitHub.
- Step 2: Create and activate a virtual environment for Python.
- Step 3: Install dependencies using pip and requirements.txt.
- Step 4: Set up the `.env` file with your Databricks host, token, and HTTP path.
- Step 5: Test your connection using `python test_connection.py`.
- Step 6: Start the server with `python main.py`.
- Step 7: Use supported MCP tools to run SQL queries, list jobs, or check job statuses via your preferred interface or LLM integration.
MCP Server for Databricks's Core Features & Benefits
The Core Features
- run_sql_query(sql: str)
- list_jobs()
- get_job_status(job_id: int)
- get_job_details(job_id: int)
The Benefits
- Enables programmatic and natural language management of Databricks resources
- Automates data querying and job monitoring
- Supports seamless integration with LLMs for intelligent interaction
- Facilitates secure and efficient workflow automation
MCP Server for Databricks's Main Use Cases & Applications
- Automated SQL querying in Databricks for data analysis
- Monitoring and managing Databricks jobs programmatically
- Integrating Databricks with NLP systems for AI-driven data management
- Streamlining data pipeline orchestration
- Enabling natural language commands to interact with Databricks environment
FAQs of MCP Server for Databricks
Developer
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