ThoughtSpot MCP Server

Table of Contents

Overview
- Supported integrations
- MCP Server license
Core components and roles
MCP Server architecture and tools
MCP Server URL
Next steps
Additional resources

ThoughtSpot’s Model Context Protocol (MCP) Server enables integration of ThoughtSpot analytics into any AI-native application, custom chatbot, or LLM platform that supports MCP. Instead of rebuilding analytics logic yourself, you connect an LLM/AI agent to the ThoughtSpot MCP Server.

Overview🔗

ThoughtSpot MCP Server exposes ThoughtSpot analytics as tools and resources that MCP-compatible agents can discover and use. When integrated, the MCP Server provides your AI agent or LLM with the following capabilities:

Automatic discovery of ThoughtSpot MCP tools
Natural language queries and responses
Programmatic creation of Liveboards and visualizations
Generating embeddable visualizations

Supported integrations🔗

ThoughtSpot MCP Server supports two primary integration options:

Integration option	Description
Plug-and-play clients	This integration works with agents or LLMs that natively support MCP, such as Claude, OpenAI, Gemini, or custom MCP clients. It allows your AI agent to call tools directly and leverage ThoughtSpot’s governed analytics, business semantic layer, data context, and row-level/object-level security, without the need to build your analytics logic. When to use: If your application already has an AI chat interface or agentic experience, you can quickly add analytics to your existing setup without custom development.
Custom chatbot integration	If you are building your own MCP-based chatbot or application with custom orchestration logic or LLM, you can integrate the ThoughtSpot MCP Server to call ThoughtSpot tools behind your own web experience. When to use: Use this option if your organization requires a custom conversation flow, backend orchestration, and a tailored analytics experience for your users.

Integration option

Description

Plug-and-play clients

This integration works with agents or LLMs that natively support MCP, such as Claude, OpenAI, Gemini, or custom MCP clients. It allows your AI agent to call tools directly and leverage ThoughtSpot’s governed analytics, business semantic layer, data context, and row-level/object-level security, without the need to build your analytics logic.

When to use: If your application already has an AI chat interface or agentic experience, you can quickly add analytics to your existing setup without custom development.

Custom chatbot integration

If you are building your own MCP-based chatbot or application with custom orchestration logic or LLM, you can integrate the ThoughtSpot MCP Server to call ThoughtSpot tools behind your own web experience.

When to use: Use this option if your organization requires a custom conversation flow, backend orchestration, and a tailored analytics experience for your users.

Regardless of integration mode, ThoughtSpot’s semantic layer, data context, and security features ensure trusted and governed analytics for all users.

MCP Server license🔗

ThoughtSpot MCP Server is available as an add-on with the following license plans:

ThoughtSpot Enterprise Edition
ThoughtSpot Embedded

To learn more about subscription options, contact your ThoughtSpot sales representative.

Core components and roles🔗

The MCP Server integration and orchestration layers include the following core components:

Component	Role
Host application	The AI platform or AI-native app that renders chat, responses, and charts, and manages user-facing conversation. For example, Claude AI web app, Claude Desktop, ChatGPT, OpenAI-based integrations, Gemini-based agents, custom web applications, or internal tools.
MCP client	The MCP client discovers available tools, manages the MCP connection to the server, and passes tool calls between the LLM and the MCP Server.
ThoughtSpot MCP Server	The remote MCP server hosted by ThoughtSpot. Acts as a gateway between the MCP client and ThoughtSpot. Exposes ThoughtSpot analytics as MCP tools. Receives tool calls, authenticates via OAuth/Bearer Token, and routes requests to ThoughtSpot.
ThoughtSpot instance	Your ThoughtSpot instance where data models, Liveboards, and security policies exist. - Executes queries and generates visualizations - Enforces data security with RLS and CLS rules. - In integrations using the MCP Server with Spotter 3 support, it provides additional capabilities such as advanced analytics, reasoning, forecasting, automatic data source selection, and deep research.

Component

Role

Host application

The AI platform or AI-native app that renders chat, responses, and charts, and manages user-facing conversation. For example, Claude AI web app, Claude Desktop, ChatGPT, OpenAI-based integrations, Gemini-based agents, custom web applications, or internal tools.

MCP client

The MCP client discovers available tools, manages the MCP connection to the server, and passes tool calls between the LLM and the MCP Server.

ThoughtSpot MCP Server

The remote MCP server hosted by ThoughtSpot.

Acts as a gateway between the MCP client and ThoughtSpot.
Exposes ThoughtSpot analytics as MCP tools.
Receives tool calls, authenticates via OAuth/Bearer Token, and routes requests to ThoughtSpot.

ThoughtSpot instance

Your ThoughtSpot instance where data models, Liveboards, and security policies exist.

- Executes queries and generates visualizations - Enforces data security with RLS and CLS rules. - In integrations using the MCP Server with Spotter 3 support, it provides additional capabilities such as advanced analytics, reasoning, forecasting, automatic data source selection, and deep research.

The following figure illustrates the interaction between the user, agent, and MCP Server:

MCP Server architecture and tools🔗

For more information about MCP tools, resources, and workflow processing, see the following documentation:

MCP Server URL🔗

ThoughtSpot MCP Server now uses date-based API versioning in the URL. New versions are identified using the ?api-version=YYYY-MM-DD parameter, which you can append to the MCP Server URL to pin your integration to a specific version. Each new version may introduce tool changes, enhancements, or bug fixes.

When you set the api-version to a specific date string, the server returns the version released on the specified date. If no new version of MCP Server is released on the date specified in the URL, the server returns the closest earlier version. For example, if you request ?api-version=2026-06-01 and no new version has been released since 2026-05-01, the server returns the 2026-05-01 version. This means your integration continues to work without breaking, and you only need to update your pinned date if you want to opt in for a newer version.

To automatically receive every new version of the MCP tools as ThoughtSpot releases them, use the URL without a pinned api-version. Note that the new versions may introduce changes to tool behavior, input parameters, or output schemas that affect your integration. Therefore, we recommend pinning your integration to a specific version.

Apps/Integration type MCP Server URL

Apps/Integration type	MCP Server URL
OAuth apps (Plug-and-play integration)	`https://agent.thoughtspot.app/mcp?api-version=latest` Always points to the latest version. `https://agent.thoughtspot.app/mcp` Currently, this URL points to the baseline version with legacy MCP tools. It will resolve to the latest version in the near future. If you want to pin a specific version, use the URL with the `api-version` parameter and specify the date string: `https://agent.thoughtspot.app/mcp?api-version={YYYY-MM-DD}`. For example, `?api-version=2026-05-01`
Bearer token apps	`https://agent.thoughtspot.app/token/mcp` Always points to the latest version. `https://agent.thoughtspot.app/token/mcp?api-version={YYYY-MM-DD}` Replace `{YYYY-MM-DD}` with the actual date string to point to the specified version or the closest earlier version. For example, `?api-version=2026-05-01`

OAuth apps
(Plug-and-play integration)

https://agent.thoughtspot.app/mcp?api-version=latest
Always points to the latest version.
https://agent.thoughtspot.app/mcp
Currently, this URL points to the baseline version with legacy MCP tools. It will resolve to the latest version in the near future.
If you want to pin a specific version, use the URL with the api-version parameter and specify the date string:
https://agent.thoughtspot.app/mcp?api-version={YYYY-MM-DD}. For example, ?api-version=2026-05-01

Bearer token apps

https://agent.thoughtspot.app/token/mcp
Always points to the latest version.
https://agent.thoughtspot.app/token/mcp?api-version={YYYY-MM-DD}
Replace {YYYY-MM-DD} with the actual date string to point to the specified version or the closest earlier version. For example, ?api-version=2026-05-01

Important

The https://agent.thoughtspot.app/openai/mcp and https://agent.thoughtspot.app/bearer/mcp are deprecated and point to the version with legacy MCP tools only. ThoughtSpot recommends migrating your existing MCP Server integration setup to the new version. For more information, see MCP Server changelog.

Next steps🔗

To learn how to connect existing MCP-aware tools such as Claude, ChatGPT, and Gemini, see the Connecting MCP clients to ThoughtSpot MCP Server documentation.
To learn how to integrate MCP Server with a custom chatbot or application, see the Integrating MCP Server in a custom chatbot documentation.

Additional resources🔗

For information about MCP, see the Model Context Protocol specification.
For implementation details, see the MCP Server GitHub repository.