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call_databricks_tool

Execute Databricks-hosted tools through the MCP proxy by specifying tool names and arguments for remote operations.

Instructions

Call a tool on the remote Databricks MCP server.

Args:
    tool_name: Name of the tool to call (use list_databricks_tools to see available tools)
    arguments: Arguments to pass to the tool

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_nameYes
argumentsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The @mcp.tool()-decorated handler function that implements the core logic of 'call_databricks_tool' by checking authentication and proxying the tool call to the DatabricksMCPProxy instance.
    @mcp.tool()
    def call_databricks_tool(tool_name: str, arguments: dict = {}) -> str:
        """
        Call a tool on the remote Databricks MCP server.
        
        Args:
            tool_name: Name of the tool to call (use list_databricks_tools to see available tools)
            arguments: Arguments to pass to the tool
        """
        if not state.authenticated or not state.proxy:
            return "Not authenticated. Call 'authenticate' first."
        
        try:
            result = state.proxy.call_tool(tool_name, arguments)
            
            if hasattr(result, 'content') and result.content:
                texts = [c.text for c in result.content if hasattr(c, 'text')]
                if texts:
                    return "\n".join(texts)
            
            return str(result)
        
        except Exception as e:
            return f"Error calling tool '{tool_name}': {e}"
  • Supporting method in DatabricksMCPProxy class that performs the actual remote tool invocation via DatabricksMCPClient.call_tool in a thread pool.
    def call_tool(self, name: str, arguments: dict) -> Any:
        """Call a tool on the remote MCP server."""
        if not self._mcp_client:
            raise RuntimeError("Not connected. Call connect() first.")
        with ThreadPoolExecutor() as executor:
            return executor.submit(self._mcp_client.call_tool, name, arguments or {}).result()
  • The @mcp.tool() decorator registers the 'call_databricks_tool' function with the FastMCP server.
    @mcp.tool()

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