Azure Databricks managed MCP servers

Important

This feature is in Public Preview.

Azure Databricks managed MCP servers are ready-to-use servers that connect your AI agents to data in Unity Catalog, Azure Databricks AI Search indexes, Genie Spaces, and custom functions. They also connect agents to common software-as-a-service (SaaS) applications like Slack and GitHub.

  • No setup: Azure Databricks hosts the servers and manages authentication.
  • Governed: Unity Catalog enforces permissions, so agents and users access only the tools and data you grant them.
  • Centralized: view, monitor, and manage every server from Unity AI Gateway.

To call these servers from agent code, see Use MCP servers in agents.

Azure Databricks also has ready-to-use MCP Services in the system.ai schema for common SaaS apps (Slack, GitHub, Google Drive, and more). See Databricks-provided MCP Services.

Available managed servers

Databricks has the following MCP servers that work out of the box. When connecting to managed MCP servers using on-behalf-of user authentication, include the corresponding OAuth scope for each server your application needs to access. For setup instructions, see Authentication methods.

Genie One

Important

This feature is in Beta.

URL pattern OAuth scope
https://<workspace-hostname>/api/2.0/mcp/genie genie

Ask natural-language data questions about your enterprise data. Genie One searches across Genie Spaces and your Unity Catalog data, then returns a grounded answer with a deep link back to the conversation in the Azure Databricks UI. Read-only.

Genie runs asynchronously. Call the genie_ask tool to start a conversation, then call genie_poll_response until the response is complete. To continue an existing conversation, pass the previous conversation_id to genie_ask.

Genie Space

URL pattern OAuth scope
https://<workspace-hostname>/api/2.0/mcp/genie/{genie_space_id} genie

Query a single Genie Space with natural language. Read-only.

The Genie Space server invokes Genie as a tool, so it doesn't pass conversation history to the Genie API. To preserve history, use Genie in a multi-agent system.

URL pattern OAuth scope
https://<workspace-hostname>/api/2.0/mcp/ai-search/{catalog}/{schema}/{index_name} ai-search

Query AI Search indexes to find relevant documents. Requires Azure Databricks managed embeddings.

AI Search was formerly Vector Search. The previous /api/2.0/mcp/vector-search/ URL prefix and vector-search scope still work.

Databricks SQL

URL pattern OAuth scope
https://<workspace-hostname>/api/2.0/mcp/sql sql

Run AI-generated SQL to create data pipelines from AI coding tools. Read and write.

Databricks SQL runs asynchronously: call the tool to start, then poll until the response completes.

Unity Catalog functions

URL pattern OAuth scope
https://<workspace-hostname>/api/2.0/mcp/functions/{catalog}/{schema}/{function_name} unity-catalog

Run Unity Catalog functions as predefined SQL tools.

Example: a customer-support agent

Connect one agent to multiple managed MCP servers:

  • AI Search (/api/2.0/mcp/ai-search/prod/customer_support) — search support tickets and documentation.
  • Genie Space (/api/2.0/mcp/genie/{billing_space_id}) — query billing data and customer information.
  • Unity Catalog functions (/api/2.0/mcp/functions/prod/billing) — run custom functions for account lookups.

This gives the agent unstructured data (tickets), structured data (billing), and custom business logic in one place.

Additional resources

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