How to Use the MonkeyLearn MCP in Cursor

Q: Does Cursor support MonkeyLearn for bulk keyword extraction?

You can use extracttext to process multiple strings during an Agent session. It handles the API calls so your code is built on real extracted entities.

Inject live text analysis into your codebase with the MonkeyLearn MCP server for Cursor.

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…and any MCP-compatible client

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Connect MonkeyLearn MCP to Cursor

Create your Vinkius account to connect MonkeyLearn to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup MonkeyLearn with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Real-time entity extraction

Call `extract_text` to pull specific data points directly into your current file. The AI uses these real responses to generate accurate code based on actual data. Stop relying on hardcoded stubs. Your editor now handles live text analysis during your coding session.

Context-aware classification

Use `classify_text` to help your agent sort logs or user inputs while you write logic. It classifies data based on your custom models, keeping your code relevant. This integration allows your agent to understand complex inputs by running them through your existing trained classifiers.

Pipeline and workflow management

View your active processes using `list_pipelines` and `list_workflows` to ensure your data flow is correct. These tools show exactly what is happening under the hood. Cursor lets you trigger these directly, giving you full visibility into your text processing stack without switching tabs.

Setup guide

Set up MonkeyLearn 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 MonkeyLearn 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 MonkeyLearn transactions." If the MCP tools are loaded correctly, Cursor will call the MonkeyLearn tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by MonkeyLearn. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about MonkeyLearn MCP in Cursor

Create an mcp.json file in your project root or global config folder. Add the server configuration there, and the tools will show up in your Agent mode.

Yes, you can pass code comments or documentation strings into the `classify_text` tool. It helps you organize your codebase notes based on your custom labels.

You can use `extract_text` to process multiple strings during an Agent session. It handles the API calls so your code is built on real extracted entities.

It uses a project-specific .cursor/mcp.json file. This allows you to commit your tool definitions directly to your repository.

The MCP server acts as a thin client that proxies your requests to the API. Your raw text is processed by the service and is not stored or persisted by the server daemon.

Use it with your favorite AI tools

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

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