How to Use the ThinkStack MCP in Cursor

Q: How can I get live data into my code using ThinkStack and Cursor?

You use sendquery. The MCP Server executes the query and returns a real-time result that the AI agent uses as context for your function. It's not simulated; it’s live.

Q: Where do I configure the sources for ThinkStack and Cursor?

You add them using addsource. This tool indexes external data, making it available to the agent mode in your code editor. You can confirm what's connected with listsources.

Q: If I need help auditing my bots using ThinkStack and Cursor, which tools should I use?

Start with listbots to see all available agents. Then, run getbot to get detailed specs on a specific bot's capabilities. This helps you structure your code calls correctly.

Q: Can the MCP Server handle multiple sources for ThinkStack and Cursor?

Yes. You can use listsources to verify that several knowledge bases are connected simultaneously, allowing your agent to draw context from multiple places when writing code.

Write code that talks to your APIs with Cursor and MCP Server tools.

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Inject Live Query Results into Code

The `send_query` tool lets you get live data from a chatbot, right when you need it. Instead of using mock data or stubs, the AI calls this function and injects real API responses directly as variables in your code block. This means if you're writing a test or a utility function, the context is accurate. The MCP Server makes sure the result from `send_query` is available for immediate use.

Contextual Coding with Source Data

Use `add_source` to feed external knowledge into your coding environment. This tool crawls documentation or databases, and the resulting context informs the AI's suggestions. You write cleaner code because the AI knows the rules. When you need specific data for a function, you can also run `list_sources` to confirm which knowledge bases are connected to this project.

Verify and Audit Tool Availability

Before writing code that depends on external services, check the tools first. Running `list_actions` shows every available function within the MCP Server. This prevents runtime errors. If you're building a complex agent flow, running `get_bot` gives you the precise metadata needed to structure your calls correctly in Python or TypeScript.

Setup guide

Set up ThinkStack MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the ThinkStack MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent ThinkStack transactions." If the MCP tools are loaded correctly, Cursor will call the ThinkStack tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "thinkstack-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about ThinkStack MCP in Cursor

You use `send_query`. The MCP Server executes the query and returns a real-time result that the AI agent uses as context for your function. It's not simulated; it’s live.

You add them using `add_source`. This tool indexes external data, making it available to the agent mode in your code editor. You can confirm what's connected with `list_sources`.

Start with `list_bots` to see all available agents. Then, run `get_bot` to get detailed specs on a specific bot's capabilities. This helps you structure your code calls correctly.

Yes. You can use `list_sources` to verify that several knowledge bases are connected simultaneously, allowing your agent to draw context from multiple places when writing code.

The server manages the structure and metadata of bot actions and conversation details. The `get_conversation` tool handles retrieving historical text context, which is sensitive user interaction data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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