MonkeyLearn MCP Server for Cursor 10 tools — connect in under 2 minutes
Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.
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{
"mcpServers": {
"monkeylearn": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
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About MonkeyLearn MCP Server
Connect your MonkeyLearn account to your AI agent and leverage powerful NLP models for text analysis and data extraction through natural conversation.
Cursor's Agent mode turns MonkeyLearn into an in-editor superpower. Ask Cursor to generate code using live data from MonkeyLearn and it fetches, processes, and writes. all in a single agentic loop. 10 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
What you can do
- Text Classification — Use pre-trained or custom classifiers for sentiment analysis, topic detection, and intent classification.
- Data Extraction — Automatically pull keywords, entities, and specific data points from raw text strings.
- Model Discovery — List and inspect all classifiers, extractors, and pipelines available in your account.
- Workflow Tracking — Monitor your automated workflows and processing activity in real-time.
- Tag Hierarchy — Access the tag trees used by your models to understand classification structures.
- Deep Inspection — Fetch detailed configuration and metadata for specific models using their unique IDs.
The MonkeyLearn MCP Server exposes 10 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect MonkeyLearn to Cursor via MCP
Follow these steps to integrate the MonkeyLearn MCP Server with Cursor.
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
Save the file
Cursor will automatically detect the new MCP server
Start using MonkeyLearn
Open Agent mode in chat and ask: "Using MonkeyLearn, help me...". 10 tools available
Why Use Cursor with the MonkeyLearn MCP Server
Cursor AI Code Editor provides unique advantages when paired with MonkeyLearn through the Model Context Protocol.
Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
MonkeyLearn + Cursor Use Cases
Practical scenarios where Cursor combined with the MonkeyLearn MCP Server delivers measurable value.
Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP
Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically
Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates
Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data
MonkeyLearn MCP Tools for Cursor (10)
These 10 tools become available when you connect MonkeyLearn to Cursor via MCP:
classify_text
Classify text using a model
extract_text
Extract data from text
get_classifier_details
Get classifier metadata
get_extractor_details
Get extractor metadata
list_activity
List account activity
list_classifiers
g., sentiment analysis, topic detection) available in your account. List available classifiers
list_extractors
g., keyword extraction, entity recognition) available in your account. List available extractors
list_pipelines
List MonkeyLearn pipelines
list_tag_trees
List available tag trees
list_workflows
List automated workflows
Example Prompts for MonkeyLearn in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with MonkeyLearn immediately.
"Classify the sentiment of this review: 'The product exceeded all my expectations, truly amazing!' using model cl_oZ9GRg8P."
"List all classifiers available in my account."
"Show me my recent processing activity."
Troubleshooting MonkeyLearn MCP Server with Cursor
Common issues when connecting MonkeyLearn to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
MonkeyLearn + Cursor FAQ
Common questions about integrating MonkeyLearn MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.Can Cursor use MCP tools in inline edits?
How do I verify MCP tools are loaded?
Connect MonkeyLearn with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect MonkeyLearn to Cursor
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.