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Vinkius

Hugging Face Connector for AI agents.

15 live capabilities

Find and test machine learning models without leaving your chat.

Live agent request Hugging Face / Connector

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Why people use Hugging Face

Hugging Face for Faster Machine Learning Model Discovery

With this Connector, you just tell your agent what you're looking for. It handles the searching, filtering, and inspection in seconds. You get a summary of the best fits, the dataset schemas, and even live inference results directly in your chat. It turns a 20-minute research task into a 30-second conversation.

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

What Vinkius changes

That this Connector turns the Hugging Face Hub into an actionable library for your AI agent.

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

One account · 5,900+ Connectors

  1. Real-world use case 01

    Finding the right model

    A developer needs a text generation model.

  2. Real-world use case 02

    Dataset vetting

    A researcher needs sentiment data.

  3. Real-world use case 03

    Quick classification

    A content moderator wants to label a batch of comments.

Complete set · 15capabilities

The complete Hugging Face capability set.

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

Capability set01 / 04

01—04

4 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 01 Capability

    List spaces

    Hugging Face list_spaces lets you search for interactive ML demo applications. This helps you find live demos to see how models perform in real-world scenarios.

  2. 02 Capability

    Check hf status

    Hugging Face check_hf_status lets you verify if the Hugging Face API is currently reachable. Use this to ensure your connection is active before starting a heavy task.

  3. 03 Capability

    Get account

    Hugging Face get_account lets you retrieve your profile information and organization details. It's useful for checking your current account status and permissions.

  4. 04 Capability

    Get dataset

    Hugging Face get_dataset lets you fetch specific details about a dataset. You can use this to inspect schemas and metadata for a particular data source.

Capability set02 / 04

05—08

4 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 05 Capability

    Run summarization

    Hugging Face run_summarization lets you execute text summarization on a provided string. This lets you get the gist of long documents using hosted models instantly.

  2. 06 Capability

    Run text generation

    Hugging Face run_text_generation lets you generate new text using a specific model. It's perfect for quick creative writing or drafting content based on a prompt.

  3. 07 Capability

    Get model

    Hugging Face get_model lets you retrieve the full details of a specific model. Use this to see the model card, author info, and usage statistics.

  4. 08 Capability

    Get space

    Hugging Face get_space lets you get specific information about an interactive demo space. This helps you understand the underlying tech of a live ML application.

Capability set03 / 04

09—12

4 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 09 Capability

    List collections

    Hugging Face list_collections lets you browse curated groups of models and datasets. This is a great way to find high-quality, human-curated resources.

  2. 10 Capability

    List datasets

    Hugging Face list_datasets lets you search the entire hub for datasets. Use this to find the raw data you need for training or fine-tuning.

  3. 11 Capability

    List models by author

    Hugging Face list_models_by_author lets you see all models uploaded by a specific user or organization. This is helpful for following specific researchers or companies.

  4. 12 Capability

    List models by task

    Hugging Face list_models_by_task lets you find models sorted by task and download count. It helps you identify the most popular capabilities for things like image recognition.

Capability set04 / 04

13—15

3 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 13 Capability

    List models

    Hugging Face list_models lets you search the general Hugging Face Hub for any model. This is your primary way to find new models based on keywords.

  2. 14 Capability

    Run text classification

    Hugging Face run_text_classification lets you classify input text into different categories. Use this to perform sentiment analysis or topic labeling on the fly.

  3. 15 Capability

    Run inference

    Hugging Face run_inference lets you run general model inference on the platform. This is the catch-all capability for getting results from any hosted model.

Set up in minutes

One URL. Then ask Hugging Face to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Hugging Face 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_xAlB3RIV4hRBFELH56Jcflb4rJWI2Wa664OkY3XX/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 Hugging Face, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Hugging Face for the conversation.

Where the request belongs

Work Hugging Face can move forward.

Built around the request

This is for ML engineers, data scientists, and NLP researchers who spend hours wading through model cards and dataset documentation to find the right components for their projects.

01

ML Engineer

Finding and testing text generation models for a new production app without manual downloads.

02

Data Scientist

Searching for specific sentiment analysis datasets and checking their metadata to see if they're clean enough for training.

03

NLP Researcher

Exploring curated collections of models to see what's trending in specific sub-fields like speech-to-text.

Build the capability set

Add more capabilities.

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

Browse Connectors
Hugging Face logo
01 15 capabilities

Hugging Face

Access thousands of pre-trained AI models for NLP, vision, and audio tasks with the largest open-source machine learning hub.

View Connector
Metatext logo
02 10 capabilities

Metatext

No-code NLP and AI model management via Metatext. run inference and manage datasets.

View Connector
Eden AI logo
03 13 capabilities

Eden AI

Access 100+ AI models through a single API. route LLMs, generate embeddings, and execute specialized AI tasks like OCR and translation.

View Connector
Together AI logo
04 7 capabilities

Together AI

Generate code, evaluate embeddings, and deploy open-source LLMs instantly from your local agent via Together AI's infrastructure.

View Connector
Replicate logo
05 12 capabilities

Replicate

Run ML models via Replicate. generate images, text, audio and video from community models, track predictions and explore collections from any AI agent.

View Connector
NVIDIA AI logo
06 9 capabilities

NVIDIA AI

Access LLMs, embeddings, code generation, and reasoning via NVIDIA API Catalog.

View Connector

Bring your own AI

Change the model, client or framework. Keep Hugging Face connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
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  • Pieces
  • Sourcegraph Cody
  • JetBrains
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  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about Hugging Face.

The practical details behind the request, access and result.

Can the Hugging Face MCP find specific models for my project?

Yes, it lets your agent search the entire Hub by keyword, author, or specific task like image generation or text classification.

How do I use the Hugging Face MCP to test model outputs?

You can ask your agent to run inference on any hosted model. It will execute the task and give you the results directly in your chat.

Can this Connector help me find datasets for training?

Yes, it can search the Hub for datasets and even pull the metadata and schemas so you can see if the data fits your needs.

Does the Hugging Face MCP work with my existing account?

It connects to your Hugging Face account, allowing your agent to see your profile, organizations, and your specific token scopes.

Can I see interactive demos with this Connector?

Yes, the Connector can search for and provide details on Spaces, which are interactive demo applications hosted on the platform.

How does the Hugging Face MCP save me time?

It eliminates the need to manually browse tabs and copy-paste model IDs. Your agent does the discovery and testing for you in one place.

Can my AI run inference on Hugging Face models?

Yes. Use run_inference, run_text_generation, run_text_classification, or run_summarization to send input to any hosted model and get results instantly.

How do I find the best model for a task?

Use list_models_by_task with a pipeline tag like 'text-generation' or 'image-classification'. Results are sorted by downloads so the most popular appear first.

Can I browse datasets and Spaces?

Yes. list_datasets and list_spaces let you search by keyword, and get_dataset / get_space return full metadata.

One connection away

Give your agent a direct line to Hugging Face.

Connect Hugging Face once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available