DatabricksClient MCP Server
The DatabricksClient API is a comprehensive RESTful service provided by Microsoft as part of the Azure Resource Manager (ARM) suite, specifically for the Azure Databricks service.
Quick Start Summary
The DatabricksClient MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the DatabricksClient API through natural language. It exposes 7 API endpoints as callable tools, such as Operations_List, Workspaces_ListBySubscription, Workspaces_ListByResourceGroup, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/azure-com-databricks. This integration is sourced from the auto DatabricksClient OpenAPI specification (v2018-04-01) and has a quality score of 34/99 (fair documentation coverage).
Server Details
- Category
- Data & Analytics
- Authentication
- None
- Endpoints
- 7 operations
- Transport
- STDIO
- Spec Version
- v2018-04-01
- Install Command
npx -y @mcp/azure-com-databricks
Environment Variables
DATABRICKSCLIENT_API_KEYExample: your_databricksclient_api_key
Top Endpoints
/providers/Microsoft.Databricks/operationsOperations_List
/subscriptions/{subscriptionId}/providers/Microsoft.Databricks/workspacesWorkspaces_ListBySubscription
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspacesWorkspaces_ListByResourceGroup
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}Workspaces_Get
/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}Workspaces_CreateOrUpdate
One-Click Install
Copy the snippet for your MCP client and paste it in — zero editing required.
Claude Desktop
Add to claude_desktop_config.json
{
"mcpServers": {
"azure-com-databricks": {
"command": "npx",
"args": [
"-y",
"@mcp/azure-com-databricks"
],
"env": {
"DATABRICKSCLIENT_API_KEY": "your_databricksclient_api_key"
}
}
}
}Cursor
Settings → MCP Servers → Add
{
"mcpServers": {
"azure-com-databricks": {
"url": "https://mcpbridge.org/config/azure-com-databricks.json"
}
}
}Saves as .cursor/mcp.json in the download. Move it to your project root.
VS Code
Use with MCP extension
{
"mcpServers": {
"azure-com-databricks": {
"url": "https://mcpbridge.org/config/azure-com-databricks.json"
}
}
}Endpoints Explorer
Search and browse the 7 operations supported by this server.
Multi-Language Code Examples
Executable code snippets for calling DatabricksClient endpoints in curl, TypeScript, or Python.
curl -X GET "https://api.apis.guru/v2/specs/azure.com/databricks/2018-04-01/swagger.json/providers/Microsoft.Databricks/operations" \ -H "Content-Type: application/json" \ # No auth required
Manual Configuration
Directly add this block to your JSON config file, or use the hosted config registry URL.
{
"mcpServers": {
"azure-com-databricks": {
"command": "npx",
"args": ["-y","@mcp/azure-com-databricks"],
"env": {
"DATABRICKSCLIENT_API_KEY": "your_databricksclient_api_key"
}
}
}
}Authentication Details
No authentication required. This MCP server runs out-of-the-box.
Documentation Links
Error Handling & HTTP Status Code Matrix
Common status codes, error causes, and resolution steps when invoking DatabricksClient endpoints.
400 Bad RequestCause: Malformed payload parameters or missing required fields.
Resolution: Verify request schema in Endpoints tab before calling tool.
401 UnauthorizedCause: Missing or invalid API key credentials.
Resolution: Set environment variable in MCP client config under env object.
403 ForbiddenCause: Insufficient scope permissions for requested resource.
Resolution: Verify key permissions in developer dashboard.
404 Not FoundCause: Resource URL path or requested entity ID does not exist.
Resolution: Check path variables and parameters.
429 Rate Limit ExceededCause: API rate limit quota exceeded.
Resolution: Implement exponential backoff retry in tool call.
500 Internal ErrorCause: Upstream server runtime fault.
Resolution: Inspect STDIO stderr output for log trace.
Quality Score
Checked against our protocol-compliance rules.
Specification Version: v2018-04-01
Page compiled on: June 13, 2026
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📖 Detailed MCP Integration Guide
A technical breakdown of capabilities, agent workflows, and security/configuration best practices.
PUT endpoint with the necessary parameters, like the resource group name and workspace configuration, potentially even suggesting reasonable defaults based on established naming conventions or organizational policies.GET call, parse the JSON response, and present a human-readable summary. Another dynamic task could be: "Create a new staging workspace named 'db-staging-eastus' in resource group 'rg-data-dev' using the same SKU as our production workspace, but disable public network access." The agent would first query the production workspace details, extract the SKU, then compose and execute a PUT request with the modified configuration. For lifecycle automation, one could say: "Archive the workspace 'db-exploration-old' by applying a tag 'Environment: Archived' and then deleting it after 7 days if not explicitly renewed." The AI could execute the PATCH to update tags and schedule a future DELETE operation, demonstrating an ability to manage multi-step, stateful processes.Similar APIs
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