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Vinkius

MonkeyLearn Connector for AI agents.

12 live capabilities

Run sentiment analysis and text classification on your data

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AI Agent

Why people use MonkeyLearn

MonkeyLearn for Solving Manual Feedback Tagging

With this Connector, you can just ask your AI agent to run classify_text on a pile of feedback. It tells you the sentiment and the main themes instantly. You get a clear picture of your customers' moods without the manual labor.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get to run complex NLP tasks using natural language instead of writing custom scripts.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 6,100+ Connectors

  1. Real-world use case 01

    Analyzing customer reviews

    A product manager wants to know if a new feature is being received well.

  2. Real-world use case 02

    Extracting SEO keywords

    A content writer needs to pull 10 specific keywords from a long blog draft.

  3. Real-world use case 03

    Checking model configurations

    A data scientist needs to see what models are active.

Complete set · 12capabilities

The complete MonkeyLearn capability set.

These are the exact actions your AI can choose when you ask it to work with MonkeyLearn.

Capability set01 / 03

01—04

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

  1. 01 Capability

    Classify text

    Use a model to categorize text. It's perfect for identifying sentiment or intent in a few seconds.

  2. 02 Capability

    Extract text entities

    Extract entities

  3. 03 Capability

    Get classifier details

    View metadata for a specific classifier. It helps you check the exact settings for your NLP models.

  4. 04 Capability

    Get extractor details

    Get the metadata for an extractor. This shows you how your data points are being pulled.

Capability set02 / 03

05—08

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

  1. 05 Capability

    List classifier tags

    List model tags

  2. 06 Capability

    List classifiers

    See all classifiers in your account. This helps you find the right model for a new project.

  3. 07 Capability

    List extractor tags

    List extractor tags

  4. 08 Capability

    List extractors

    List all the extractors you have. Use this to see what data you can currently pull from text.

Capability set03 / 03

09—12

4 capabilities in this set.

Part of 12 available through MonkeyLearn.

  1. 09 Capability

    List model versions

    List model versions

  2. 10 Capability

    List nlp workflows

    List account workflows

  3. 11 Capability

    Run workflow

    Run NLP workflow

  4. 12 Capability

    Get api status

    Get account status

Set up in minutes

One URL. Then ask MonkeyLearn to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use MonkeyLearn from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_ajv6syROl8nKEZz1ZGobS0MBFBO5sLwE0cSqFWQ2/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it MonkeyLearn, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable MonkeyLearn for the conversation.

Where the request belongs

Work MonkeyLearn can move forward.

Built around the request

This is for the data pro who needs to make sense of human language without building their own models from scratch. It's for people who need to turn thousands of comments into actionable data points quickly.

01

Data Scientist

You'll use this to test how your existing NLP models handle new samples of text without writing boilerplate code.

02

Product Manager

You'll use this to quickly summarize customer sentiment from reviews or feedback logs during a sprint.

03

Content Strategist

You'll use this to pull SEO keywords and entities from draft content to ensure it hits the right targets.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
MonkeyLearn logo
01 3 capabilities

MonkeyLearn

Automate text analysis via MonkeyLearn. classify sentiment, extract keywords, and run custom NLP pipelines directly from any AI agent.

View Connector
MeaningCloud logo
02 6 capabilities

MeaningCloud

Advanced text analytics for sentiment analysis, topic extraction, language detection, and automatic summarization.

View Connector
NLP Cloud logo
03 6 capabilities

NLP Cloud

High-performance NLP API for text summarization, entity extraction, classification, sentiment analysis, ASR, and translation.

View Connector
TextRazor logo
04 11 capabilities

TextRazor

Advanced Natural Language Processing (NLP) to extract entities, topics, and relations from text or URLs.

View Connector
Deep Talk logo
05 5 capabilities

Deep Talk

Equip your AI agent to analyze conversation datasets, extract topics, and monitor sentiment via the Deep Talk API.

View Connector
DeepOpinion (No-code NLP & Text AI API) logo
06 3 capabilities

DeepOpinion (No-code NLP & Text AI API)

Automate NLP and text analysis with DeepOpinion. list custom models, run single predictions, and process text batches directly from your AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep MonkeyLearn connected.

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Before you connect

Questions about MonkeyLearn.

The practical details behind the request, access and result.

Can I use MonkeyLearn MCP to see if my reviews are positive?

Yes, it lets you run sentiment analysis on any text you provide. Your agent can process a list of reviews and tell you the overall mood and specific highlights.

How do I see what models I have in MonkeyLearn?

You can ask your agent to list all your classifiers. It will show you every model in your account, like sentiment analysis or topic detection, so you can pick the right one.

Can this Connector help me pull specific data from a paragraph?

Definitely. You can use it to extract keywords, dates, or entities from raw text. Your agent will return a clean list of the data points you asked for.

Is MonkeyLearn MCP good for tracking my API usage?

Yes, you can ask the agent to show your recent activity. It will pull the latest logs from your account so you can see how many calls you've made and which models you're using most.

Can I see how my models are organized?

You can ask your agent to show your tag trees. It'll pull the hierarchy from your account so you can see exactly how your data is being categorized.

Does MonkeyLearn MCP work with my current account?

Yes, it connects directly to your existing MonkeyLearn account using your API key. You keep all your models and data, but gain a new way to interact with them.

Where do I find my MonkeyLearn API Key?

Log in to MonkeyLearn and go to your API Settings page. You'll find your personal API Key there.

Can I use custom models I've trained myself?

Yes! The classify_text and extract_text capabilities work with both pre-trained models and any custom models you have created in your account. Just provide the specific Model ID.

What is a Pipeline in MonkeyLearn?

Pipelines allow you to chain multiple processing steps together (e.g., classification followed by extraction). You can use the list_pipelines capability to see what's available in your account.

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.

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