How do I connect my existing MonkeyLearn models?

Once you provide your API key to the MCP, your AI client can see and use all your existing classifiers, extractors, and workflows.

Which AI clients can I use with this MCP?

You can use this with any MCP-compatible client, including Claude, Cursor, and Windsurf.

Do I need to write Python code to run these models?

No. You use natural language to tell your AI agent to run the capabilities, which then executes the models for you.

Can I run multi-step processes?

Yes, you can use the run_workflow capability to trigger complex Studio workflows you have already configured.

What kind of data can be extracted?

The MCP can extract any entities your MonkeyLearn extractors are trained to find, such as names, locations, or keywords.

Can I classify text by sentiment or topic?

Yes. Point to any classifier model ID and pass text to get classification results with confidence scores.

How does MonkeyLearn authentication work?

MonkeyLearn uses Authorization: Token {API_KEY} header against api.monkeylearn.com/v3.

Can I extract named entities from text?

Yes. Use an extractor model to pull keywords, people names, organizations, locations, and more from raw text.

An astronaut overseeing a futuristic data hub

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Connect MonkeyLearn to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn raw text into structured data using your AI agent.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 12 capabilities

We ship only the actions that matter.

Capability set01 / 03

01-04

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

01
Get classifier details
This capability retrieves specific information about a single classifier model.
02
List classifiers
This capability provides a full list of your available text classifiers.
03
List extractor tags
Get a list of all tags used within your entity extraction models.
04
List extractors
This capability returns a list of all your configured text extractors.

Capability set02 / 03

05-08

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

05
Get extractor details
This capability fetches detailed configuration info for a specific extractor.
06
List nlp workflows
This capability lists the multi-step Studio workflows you have set up.
07
List classifier tags
Use this to see all the tags associated with your classifier models.
08
Classify text
This capability sends text to your MonkeyLearn classifiers to determine sentiment, topic, or intent.

Capability set03 / 03

09-12

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

09
Extract text entities
Use this to pull structured data like names, dates, or locations from a block of text.
10
Get API status
Check the current connectivity and status of your MonkeyLearn API account.
11
List model versions
Check the different versions of your machine learning models.
12
Run workflow
Trigger a specific multi-step NLP workflow to process text through a pipeline.

Real work

What teams actually run

Customer Feedback Analysis

Automatically categorize incoming reviews into sentiment or topic buckets.

Support Ticket Routing

Identify the intent of a support request to route it to the right team.

Data Extraction

Pull specific entities like company names or dates from large datasets.

Survey Insight Generation

Process survey responses to find recurring themes and keywords.

Automate a task

Put MonkeyLearn to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

MonkeyLearn works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put MonkeyLearn to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

846ms average. Fast in production.

MonkeyLearn is checked daily against the live service.

Daily averagePeak 981ms

Oct 3Today

Fastest day: 717ms
Slowest day: 981ms
14-day trend: Slowing+5%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 12 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of MonkeyLearn, so you can see the experience inside your AI.

It does not authenticate your account with MonkeyLearn. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

MonkeyLearn Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_ajv6syROl8nKEZz1ZGobS0MBFBO5sLwE0cSqFWQ2/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — MonkeyLearn capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "monkeylearn-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ajv6syROl8nKEZz1ZGobS0MBFBO5sLwE0cSqFWQ2/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up MonkeyLearn in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work MonkeyLearn owners hand off.

Professionals who need to turn large amounts of text into structured data without writing code.

01
Data Scientists
They use the MCP to run NLP models through natural language instead of manual scripting.
02
Product Teams
They use it to automatically classify user feedback and support tickets.
03
Marketers
They use the capability to pull insights from survey responses and customer reviews.

FAQ

Questions MonkeyLearn owners ask.

01
How do I connect my existing MonkeyLearn models?
Once you provide your API key to the MCP, your AI client can see and use all your existing classifiers, extractors, and workflows.
02
Which AI clients can I use with this MCP?
You can use this with any MCP-compatible client, including Claude, Cursor, and Windsurf.
03
Do I need to write Python code to run these models?
No. You use natural language to tell your AI agent to run the capabilities, which then executes the models for you.
04
Can I run multi-step processes?
Yes, you can use the run_workflow capability to trigger complex Studio workflows you have already configured.
05
What kind of data can be extracted?
The MCP can extract any entities your MonkeyLearn extractors are trained to find, such as names, locations, or keywords.
06
Can I classify text by sentiment or topic?
Yes. Point to any classifier model ID and pass text to get classification results with confidence scores.
07
How does MonkeyLearn authentication work?
MonkeyLearn uses Authorization: Token {API_KEY} header against api.monkeylearn.com/v3.
08
Can I extract named entities from text?
Yes. Use an extractor model to pull keywords, people names, organizations, locations, and more from raw text.

Explore

More in Customer Support

Connect MonkeyLearn to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Get classifier details

List classifiers

List extractor tags

List extractors

05-08

Get extractor details

List nlp workflows

List classifier tags

Classify text

09-12

Extract text entities

Get API status

List model versions

Run workflow

What teams actually run

Customer Feedback Analysis

Support Ticket Routing

Data Extraction

Survey Insight Generation

Building your own app? The connector is yours to use.

MonkeyLearn Connector

Claude Desktop

Data Scientists

Product Teams

Marketers

How do I connect my existing MonkeyLearn models?

Which AI clients can I use with this MCP?

Do I need to write Python code to run these models?

Can I run multi-step processes?

What kind of data can be extracted?

Can I classify text by sentiment or topic?

How does MonkeyLearn authentication work?

Can I extract named entities from text?

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