Model Context Protocol (MCP) on Databricks
This page is an overview of the MCP options on Databricks. MCP is an open source standard that connects AI agents to tools, resources, prompts, and other contextual information.
The main benefit of MCP is standardization. You can create a tool once and use it with any agent—whether it's one you've built or a third-party agent. Similarly, you can use tools developed by others, either from your team or from outside your organization.
Databricks-managed vs. custom-hosted MCP servers
Databricks provides two MCP options:
Aspect | Databricks-managed MCP servers | Custom MCP servers |
|---|---|---|
Intended use case | Databricks has ready-to-use servers that let agents query data and access tools in Unity Catalog. | Securely host your own MCP server as a Databricks app to bring your own server or run a third-party MCP server. |
Available tools | Expose specific Databricks services as MCP resources:
| Bring your own custom tools and specialized business logic |
Setup complexity | Ready to use immediately | Requires app deployment |
Security model | Unity Catalog permissions are always enforced, so agents and users can only access tools and data they're allowed to. | You configure authentication and authorization |
Authorization methods | Supports OAuth and PAT authentication to connect to clients like Cursor and Claude Desktop | Only supports OAuth, which is unsupported by some clients like Cursor and Claude Desktop |
Compute pricing
Compute pricing for managed MCP servers depends on the MCP workloads:
-
Unity Catalog functions use serverless general compute. See serverless compute pricing.
-
Genie uses serverless SQL compute to run. See Serverless SQL pricing.
Custom MCP servers are subject to Databricks Apps pricing.