An MCP server connecting to Databricks API, allowing large language models (LLMs) to run SQL queries, list jobs, and retrieve job status from Databricks environments.
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A server implementing the MCP protocol to connect with Databricks Genie API, enabling LLMs to ask questions, execute SQL, and interact with Databricks conversational agents.
A Model Context Protocol (MCP) server for executing SQL queries against Databricks using the Statement Execution API. Enables AI assistants to directly query Databricks data warehouses, analyze schemas, and retrieve structured results.
An MCP server that allows LLMs and AI tools to search and read academic papers from arXiv, following the MCP server pattern.
An MCP server to search and access medical and life sciences papers from PubMed, designed for integration in the MCP ecosystem.
An MCP server for reading .ged files and genetic data, integrating ancestry information into AI workflows via MCP.
An MCP server that enables AI assistants to search and access arXiv research papers through a simple Message Control Protocol interface, allowing for paper search, download, listing, and reading capabilities. Highly relevant as a specialized MCP server.
A Model Context Protocol (MCP) server that connects to the Databricks API, enabling large language models (LLMs) to interact with Databricks environments for data access and job management.
run_sql_query(sql: str) – Execute SQL querieslist_jobs() – List jobsget_job_status(job_id: int) – Get status of a jobget_job_details(job_id: int) – Get job details.env file with Databricks credentialspython main.pypython test_connection.py.env file and avoid committing secrets to version controlhttps://github.com/JordiNeil/mcp-databricks-server
Data Access & Integration MCP Servers
mcp, databricks, data-access, sql, llm
No pricing information is provided; this appears to be an open-source project.