Connect Claude desktop

Use Claude desktop in Code or Cowork with models, MCP tools, and skills through Unity Gateway. Claude desktop also supports Anthropic subscription relay.

Prerequisites

You need your Azure Databricks workspace URL, access to the models and tools you want to use, and the latest version of Claude desktop.

On Windows, open Claude desktop at least one time before running ug configure so the app initializes its local data.

If you plan to use an Anthropic subscription relay, install the Claude Code CLI.

Connect with the Unity Gateway CLI (Recommended)

Install ug, then run this command in an interactive terminal:

ug configure --agents claude

Select your workspace and sign in. This command configures both Claude Code and the installed Claude desktop work agent for the same workspace. ug creates and selects a Claude desktop profile with the models, MCP servers, skills, and credential refresh settings available through your workspace.

Open or restart Claude desktop, then start a conversation in Code or Cowork. Use the model picker to change models.

Deploy with MDM

To deploy Claude desktop across your organization with mobile device management (MDM), see Anthropic's MDM deployment guide.

Supported features and limitations

This setup uses Claude desktop's third-party inference mode.

Manual setup

Use this setup only if you can't use ug. It requires an OAuth client ID and a manually configured Claude desktop profile.

1. Get an OAuth client ID

Use the default Claude client ID, https://claude.ai/oauth/mcp-oauth-client-metadata. An account admin doesn't need to create an OAuth app. See Default OAuth client IDs.

2. Connect to Unity Gateway

From Claude desktop's sign-in screen, select Help > Troubleshooting > Enable Developer Mode, then Developer > Configure Third-Party Inference.

On the Connection page, select Gateway and enter:

Replace <workspace-hostname> with your Azure Databricks workspace hostname. Leave other settings at their defaults. See Anthropic's gateway configuration for field details.

Select Test connection and sign in to Azure Databricks. Select Apply Changes, then Save & Restart. On the sign-in screen, choose the third-party configuration and start a conversation in Code or Cowork.

3. Add MCP tools and skills

Open Developer > Configure Third-Party Inference > Connectors. Under Managed MCP servers, add an entry for each MCP or skill registry you want to use.

Use these settings for both types of connector:

For an MCP, find its three-part name under Unity Gateway > MCPs in your workspace. Give the connector a descriptive name, set Callback port to 53180, and use this URL:

https://<workspace-hostname>/ai-gateway/mcp-services/<catalog>.<schema>.<service-name>?o=<workspace-id>

For skills, name the connector databricks-skill-registry, set Callback port to 53280, and use:

https://<workspace-hostname>/ai-gateway/skills/?schema=<catalog>.<schema>

Keep the trailing slash before ?schema. To include multiple schemas, repeat the parameter: ?schema=main.default&schema=ml.prod. These skills are exposed to Claude as tools through the connector.

For each connector, select Sign in & test and complete sign-in. Select Apply Changes, then Save & Restart. Ask Claude to use a connected tool or a skill by its full name. See Add tools and skills for access requirements and more options.

Connect MCP tools with your Claude account

For system.ai.dbsql, first enable the Unity Gateway beta.

Use a custom connector to add Azure Databricks MCP tools to Claude on the web or desktop using your Claude account.

1. In Claude, open Settings > Connectors > Add custom connector.

2. Enter the MCP URL:

   https://<workspace-hostname>/ai-gateway/mcp-services/<catalog>.<schema>.<service>?o=<workspace-id>
   

3. For the OAuth client ID, enter the default Claude client ID, https://claude.ai/oauth/mcp-oauth-client-metadata. Select Add and complete sign-in.

4. In a conversation, enable the connector and ask Claude to call one of its tools. For system.ai.dbsql, try SELECT 1 AS result.

If your workspace restricts incoming IPs, allow Claude's outbound IPs. See MCP authentication for permissions, provider login, and troubleshooting.

{
  "mcpServers": {
    "databricks-tools": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://<workspace-hostname>/ai-gateway/mcp-services/<catalog>.<schema>.<service>?o=<workspace-id>",
        "--header",
        "Authorization: Bearer <databricks-pat>"
      ]
    }
  }
}

Troubleshooting

• Sign-in fails: For manual setup, check the client ID, /oidc issuer, and ai-gateway scope. The registered redirect URL must match the connector's host and port: 53180 for models and MCPs, or 53280 for skills in this guide. OAuth application changes can take up to 30 minutes to take effect.

• A model is missing: Check your model permissions and rerun ug configure --agents claude to refresh the desktop model list. For manual setup, add the model's full Unity Catalog name under Connection > Models > Model list. An explicit list replaces automatic discovery, so include the models you want to use. Apply the changes and restart.

• An MCP or skill connector fails: Check its URL and permissions. For manual setup, the Authorization server field must contain the JSON array shown above. Select Sign in & test to inspect the error.

• Workspace sign-in works, but a tool asks you to log in: Open the login link returned by the MCP, sign in to the external provider, then retry the call. Workspace and provider sign-in are separate steps.

Next steps

• Connect Claude Code
• Add tools and skills
• ug CLI reference