Discover 28 MCPs built for Databricks.
Accelerates development with Python for the Databricks Lakehouse, covering all public Databricks REST API operations.
Connect AI agents to Databricks for enterprise data access and developer automation.
Connects LLMs to Databricks, enabling natural language interaction with SQL warehouses and job management.
Enables interaction with Databricks clusters, jobs, and notebooks via the Model Completion Protocol.
Enables LLMs to interact with Databricks clusters, jobs, notebooks, and more via the Model Completion Protocol (MCP).
Executes SQL queries against Databricks using the Statement Execution API.
Enables AI assistants to securely interact with Databricks workspaces by hosting Model Context Protocol (MCP) prompts and tools on Databricks Apps.
Enables interaction with Databricks workspaces via the Model Context Protocol (MCP).
Enables large language models to interact with Databricks clusters, jobs, notebooks, and SQL functionalities through the Model Completion Protocol.
Enables AI assistants to host and interact with Model Context Protocol prompts and tools directly on Databricks Apps.
Provides a custom Databricks server to test Model Context Protocol (MCP) integrations and On-Behalf-Of (OBO) authentication.
Enables connecting to Databricks data from applications like Claude Desktop through CData JDBC Drivers via a read-only Model Context Protocol (MCP) server.
Executes Databricks SQL queries and facilitates comparison of table data via a Model Context Protocol server.
Integrates AI assistants like Claude with Databricks workspaces by hosting Model Context Protocol prompts and tools on Databricks Apps.
Discover, register, and manage external API endpoints through an AI-powered chat interface within Databricks Apps.
Integrates a custom agent server with the WAF framework using SQL queries.
Establishes a secure, authenticated bridge between AI assistants and Databricks workspaces by hosting Model Context Protocol (MCP) prompts and tools on Databricks Apps.
Enables AI assistants like Claude to interact with Databricks workspaces by hosting Model Context Protocol (MCP) prompts and tools on Databricks Apps.
Exposes Databricks functionality as a Model Completion Protocol (MCP) server, enabling LLM-powered tools to interact with Databricks resources.
Enables AI assistants to securely interact with Databricks workspaces by hosting Model Context Protocol (MCP) prompts and tools on Databricks Apps.
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