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Vinkius

Hugging Face Connector for AI agents.

15 live capabilities

Search and inspect machine learning models and datasets without leaving your chat.

Live agent request Hugging Face / Connector

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AI Agent

Why people use Hugging Face

Hugging Face for Faster Model Discovery and ML Research

With this Connector, you just tell your agent what you need. It searches the Hub, pulls the metadata, checks the tags, and reports back with a summarized list of the best options. You go from hunting for a model to selecting one in a single conversation.

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

What Vinkius changes

You get to skip the manual browsing and let your agent handle the model discovery.

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 a production-ready model

    An engineer asks the agent to find a text-generation model with over 10k likes and PyTorch support to ensure it meets the team's stability standards.

  2. Real-world use case 02

    Pre-downloading dataset audits

    A researcher wants to see the file tree of a large dataset to ensure it includes the correct Parquet files before starting a heavy download.

  3. Real-world use case 03

    Troubleshooting community issues

    A developer wants to see if others are reporting memory errors on a specific Llama-3 variant before they begin fine-tuning.

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 collections

    Browse all available collections on the Hub with options to filter by author. This helps you discover curated content for specific research areas.

  2. 02 Capability

    List datasets

    Search for datasets using keywords, authors, or specific limits. This makes it easy to find the right data for your training pipeline.

  3. 03 Capability

    List spaces

    Find demo apps and Spaces filtered by search terms or SDK types like Gradio. This helps you find live examples of models in action.

  4. 04 Capability

    Run text classification

    Classify text

Capability set02 / 04

05—08

4 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 05 Capability

    List models

    Search the entire Hub for models based on task, author, or popularity. This is the fastest way to find a model that fits your specific requirements.

  2. 06 Capability

    Run inference

    Run model inference

  3. 07 Capability

    Run summarization

    Summarize text

  4. 08 Capability

    Check hf status

    Verify API connectivity

Capability set03 / 04

09—12

4 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 09 Capability

    Get account

    Get account info

  2. 10 Capability

    Get dataset

    Get dataset details

  3. 11 Capability

    Get model

    Fetch the full metadata and details for a specific model ID on the Hub. You can quickly see the author, license, and other key attributes.

  4. 12 Capability

    Get space

    Retrieve the details and runtime information for a specific Hugging Face Space. You can check if a demo is currently active before you try to use it.

Capability set04 / 04

13—15

3 capabilities in this set.

Part of 15 available through Hugging Face.

  1. 13 Capability

    List models by author

    List models by author

  2. 14 Capability

    List models by task

    ) Sorted by downloads. List models by task

  3. 15 Capability

    Run text generation

    Generate text with a 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_FxkKVF0veJdw8titnLjl9u2iYyfqdlrrRTBcGZ2c/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 and researchers who spend hours hunting for the right weights or verifying dataset structures. It solves the problem of constant context switching between the Hub and your local environment.

01

ML Engineer

The person who needs to know if a model's config file actually contains the right parameters before they start a training run.

02

AI Researcher

The person who needs to find specific datasets and read through community bug reports to see if a model is actually production-ready.

03

App Developer

The person who wants to quickly check if a Space is currently running or find a demo to see how a model behaves in real-time.

When one Connector is not enough

Combine Hugging Face with the systems that finish the task.

View all recipes
01

Connectors for Side-by-Side AI Model Evaluation

You read 15 model cards to pick a model, run zero benchmarks, and hope the one with the most likes is actually the best for your use case , because setting up evaluation infrastructure takes longer than building the product

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
Replicate logo
02 12 capabilities

Replicate

Equip your AI to dynamically search, run, and monitor thousands of open-source machine learning models hosted on Replicate via simple text commands.

View Connector
Metatext logo
03 10 capabilities

Metatext

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

View Connector
Braintrust logo
04 10 capabilities

Braintrust

Automate AI evaluations with Braintrust. organize projects, test model datasets, run benchmarks, and manage prompts via any AI agent.

View Connector
OpenAI logo
05 13 capabilities

OpenAI

Manage OpenAI resources via API. list models, monitor fine-tunes, manage batches and inspect Assistants from any AI agent.

View Connector
Together AI logo
06 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

Bring your own AI

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

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Before you connect

Questions about Hugging Face.

The practical details behind the request, access and result.

Can the Hugging Face MCP help me find specific AI models?

Yes, it allows your agent to search the entire Hub by task, author, or popularity. It can also filter by specific frameworks like PyTorch or TensorFlow.

Does this Connector let me see what's inside a dataset before I download it?

Exactly. It can list all files in a dataset repository, including subdirectories, so you can verify the structure and file types first.

Can I use the Hugging Face MCP to check if a model is production-ready?

You can use it to read community discussions, check like counts, and inspect metadata tags to see how other developers are using the model.

Can I browse curated collections of models with this Connector?

Yes, it can list and retrieve details for curated collections, making it easier to find high-quality groups of models organized by topic.

Does this Connector work with my existing AI client?

Yes, it works with any MCP-compatible client like Claude, Cursor, or Windsurf. You just need to provide your Hugging Face Access Token.

Can I check if a Hugging Face Space is actually running?

Yes, the Connector can retrieve details for specific Spaces, including their current runtime status and the SDK they use, such as Gradio or Streamlit.

How do I get a Hugging Face Access Token?

Log in to Hugging Face, go to Settings > Access Tokens, click New token, give it a name and select scopes (read is sufficient for browsing, write if you need to create repos). Copy the token immediately. it starts with hf_.

Can I search models by task type (e.g. text-generation)?

Yes! Use list_models with a search query. While the search endpoint doesn't directly filter by pipeline_tag, you can search by task name (e.g. search='text-generation') and then use get_model or get_model_tags to verify the pipeline_tag of specific models.

Can I see what files are in a model repository?

Yes! Use list_model_files with the model ID (e.g. 'google-bert/bert-base-uncased') to see the complete file tree including model weights (.safetensors, .bin), config files, tokenizer files and README. Optionally set a path to browse a specific subdirectory like 'onnx' or 'pytorch'.

Can I create discussions on model pages?

Yes! Use create_discussion with the repo type ('model', 'dataset' or 'space'), the repo ID and a title. This creates a new discussion thread on the repository. You can use list_model_discussions first to check existing threads before creating a new one.

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.

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