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This page describes how to ground responses with real-time information from the web on Azure Databricks. Use a web search server with Model Context Protocol (MCP) to connect MCP-compatible clients and agents to web search tools.
Tip
Genie Code (Agent mode) can do this for you. Try this example prompt:
Query the databricks-gemini-3-1-pro model using the OpenAI client with the google_search parameter enabled, ask a question about a current event, and print the response.
What is web search?
Web search allows foundation models to retrieve up-to-date information from the internet during response generation. When web search is enabled, the model can search the web to find relevant information and incorporate it into its response. This is useful for questions about current events, recent data, or any topic where real-time information improves the response.
Use web search
Enable web search for MCP-compatible clients and agents by using a web search MCP server, such as You.com from Azure Databricks Marketplace.
Web search through MCP
MCP-compatible clients and agents can call a web search tool independently of their model provider. Connect your client or agent to a web search MCP service or server using MCP.
Anthropic's native web search tool is not available through Azure Databricks Foundation Model APIs. Use MCP to provide web search tools to agents that use Anthropic models.
Set up the You.com MCP server
You.com is a third-party alternative for MCP-compatible clients and agents.
- Navigate to Marketplace > Agents > MCP Servers in your Azure Databricks workspace.
- Search for You.com and click Install.
- Configure the connection:
- Connection name: Enter a name (for example,
youcom_web_search). - Bearer token: Enter your You.com API key.
- Click Install.
- Grant USE CONNECTION privileges to appropriate users or groups under Catalog > Connections > [your connection] > Permissions.
After setup, the MCP server is available as a tool in AI Playground, agents, and other MCP-compatible clients. The proxy endpoint URL for your connection is:
https://<workspace_host>.databricks.com/api/2.0/mcp/external/<connection_name>
Use You.com with Claude Code
To use You.com with Claude Code and Azure Databricks Foundation Model APIs, add the You.com MCP server:
claude mcp add youcom-search \
--transport http \
--url "https://<workspace_host>.databricks.com/api/2.0/mcp/external/<connection_name>" \
--header "Authorization: Bearer <your-databricks-pat>"
Verify the server was added with claude mcp list.
Alternatively, add the server directly to ~/.claude.json:
{
"mcpServers": {
"youcom-search": {
"type": "http",
"url": "https://<workspace_host>.databricks.com/api/2.0/mcp/external/<connection_name>",
"headers": {
"Authorization": "Bearer <your-databricks-pat>"
}
}
}
}
Supported models
MCP web search requires a client or agent that can call MCP tools. It is not limited to a specific model provider. For agent integration, see Use MCP tools in a Python agent.
Data privacy and retention
When you enable web search through Azure Databricks Foundation Model APIs, the search runs on a Azure Databricks-hosted foundation model endpoint. The search query and results are processed by the hosted model regardless of which model your application calls. The same data-protection and retention terms that govern Model Serving apply to these requests:
- Azure Databricks does not use inputs sent to Model Serving, or outputs from it, to train models. See Model Serving data protection.
- Any temporary storage for abuse detection is kept in the same region as your workspace and is time-bounded. See Data retention.
The model formulates search queries from your prompt and sends them to an external search provider to retrieve results. Treat prompt content that reaches web search as data that leaves Azure Databricks for the search provider, and scope what your application sends accordingly.
Limitations
- Web search is not available for workspaces with HIPAA/BAA compliance enabled because web search queries are sent to external search services that are not HIPAA-compliant.
- Web search results depend on the model's ability to formulate search queries and synthesize results. Response quality may vary.