Integrate SpotterCode with your IDE

Table of Contents

Before you begin
Integrate SpotterCode with Cursor
- Using one-click installation
- Using the mcp.json file
Integrate SpotterCode with Claude
Integrate SpotterCode with Visual Studio Code
Verify the integration
Additional resources

This guide walks you through the process of adding SpotterCode to your IDE.

Before you begin🔗

Ensure that your IDE is AI-native and supports chat sessions with AI models.
Ensure that you have the necessary permissions to configure Model Context Protocol (MCP) servers in your IDE.
Ensure that the latest version of Node.js is installed in your environment. This is required for building embedding code with the SDK.
Ensure that you have access to a ThoughtSpot instance and can view the objects and resources that you want to embed or access via the REST API.

Integrate SpotterCode with Cursor🔗

You can add the SpotterCode MCP Server URL to Cursor using the one-click installation link or the mcp.json file.

Using one-click installation🔗

Via Cursor Marketplace

SpotterCode is available as an official plugin in the Cursor Marketplace. To install SpotterCode from the Cursor Marketplace:

Go to Cursor Marketplace.
Ensure that you are signed in, and then click Add to Cursor → Add Plugin.
To view the plugin in Cursor, click View in Editor.

Via installation link

Copy the following link and open it in Cursor:

cursor://anysphere.cursor-deeplink/mcp/install?name=SpotterCode&config=eyJ1cmwiOiJodHRwczovL3Nwb3R0ZXJjb2RlLnRob3VnaHRzcG90LmFwcC9tY3AifQ==
Cursor opens the MCP server installation page to add SpotterCode.
Click Install.

Using the mcp.json file🔗

Cursor also allows you to integrate SpotterCode by adding the MCP server URL in the mcp.json file. To add the URL:

Go to Cursor Settings > Tools and MCP. Cursor opens the mcp.json file.

Add the SpotterCode MCP Server URL as a remote MCP server.

{
  "mcpServers": {
    "SpotterCode": {
      "url": "https://spottercode.thoughtspot.app/mcp"
    }
  }
}

Click Save and close the mcp.json file. This installs the SpotterCode MCP server and makes its tools available for AI models in Cursor.

For information about configuring MCP servers in Cursor, refer to the Cursor Documentation.

Integrate SpotterCode with Claude🔗

If your Claude account includes access to Claude AI (web chat), you can add SpotterCode as a remote MCP connector. Connectors added in Claude AI automatically sync to Claude Code without any additional configuration.

For the Claude Code-only setup, you must manually point Claude Code to the SpotterCode MCP server via CLI.

Claude AI integration🔗

To add SpotterCode as a custom connector:

Go to Customize > Connectors
Click the + icon and select Add custom connector.
Enter the SpotterCode MCP server URL: https://spottercode.thoughtspot.app/mcp.
Click Add.

This configuration automatically enables SpotterCode in Claude AI chat and Claude Code for users of the Claude account.

Claude Code-only setup🔗

To enable SpotterCode in Claude Code, add the MCP server URL using the following claude mcp add command in the Claude Code CLI.

claude mcp add --transport http SpotterCode https://spottercode.thoughtspot.app/mcp

Claude Desktop integration🔗

If you are using Claude Desktop, add the URL directly to the Claude configuration JSON file:

{
  "mcpServers": {
    "SpotterCode": {
      "url": "https://spottercode.thoughtspot.app/mcp"
    }
  }
}

Claude Cowork integration🔗

If you are using Claude Cowork with Claude AI or Claude Desktop, verify whether the SpotterCode MCP connector is enabled for Claude Cowork. If it’s not enabled, add the SpotterCode MCP server:

Open Claude Cowork either in Claude AI or Claude Desktop app.
Navigate to Settings > Connectors > Customize.
If SpotterCode is already available in your organization’s list of connectors, select the SpotterCode connector. If it’s not available:
1. Click the + icon and select Add custom connector.
2. Add the SpotterCode MCP server URL: https://spottercode.thoughtspot.app/mcp.

Integrate SpotterCode with Visual Studio Code🔗

Although you can configure the MCP server in Visual Studio Code, to start a chat session with the AI agent, you’ll need GitHub Copilot or a similar extension.

To add the SpotterCode MCP Server to Visual Studio Code, use the Extensions view or the MCP: Add Server command via the Command Palette. Alternatively, directly edit the mcp.json file in your workspace configuration.

{
  "servers": {
    "SpotterCode": {
      "url": "https://spottercode.thoughtspot.app/mcp",
      "type": "http"
    }
  }
}

After you add the MCP server URL, the SpotterCode MCP server is available in the Extensions view. For more information about configuring MCP servers in Visual Studio Code, refer to Visual Studio Code Documentation.

Verify the integration🔗

To verify the integration:

Open your application project in your IDE.

If the integration is successful, you’ll see SpotterCode in the MCP servers list.
Verify the available SpotterCode skills.

For example, Cursor shows the skills of MCP connectors in the Tools and MCP page. Check if the SpotterCode MCP skills appear under SpotterCode. As you hover over each skill, you can view the description and input schema used for agentic interactions. You can also disable the MCP skills that you don’t want the AI model to use.
Initiate a chat session and ask a question related to ThoughtSpot embedding, REST APIs, or the SDKs.

In the following example, a chat session with Cursor AI is initiated with the prompt, "I want to embed a ThoughtSpot Liveboard in my React application. Use the available tools to get this information and generate the embed code". Notice how the AI agent uses the SpotterCode skills to get the required information:
Verify that the AI agent is able to discover SpotterCode skills and is using these skills to generate a response.
Review the response returned for your prompt and verify the results.

The following example shows how Cursor AI scaffolds the embed code using the SpotterCode skills. Notice that the AI agent identifies and lists the minimum configuration settings, such as the ThoughtSpot host URL, Liveboard ID, and authentication attributes, required to complete the embedding.
When you are prompted to provide additional information, specify these details to continue with the embedding as shown in the following example:
Try additional prompts such as adding custom styles, hiding UI menu actions, and more.

Additional resources🔗

For prompt examples, see Prompt examples and best practices.
For troubleshooting tips and workarounds, refer to the Troubleshooting section.