Vinkius

Hugging Face MCP. Research Models, Datasets, and Spaces Instantly.

Hugging Face MCP connects your AI agent directly to the world's largest hub for machine learning resources. Use it to find, inspect, and manage thousands of models, datasets, and live demo apps in one conversation. You can search by task type, review model file structures without downloading anything, track community discussions, or list available datasets—all from your preferred AI client.

Hugging Face MCP is compatible with Claude Claude
Hugging Face MCP is compatible with ChatGPT ChatGPT
Hugging Face MCP is compatible with Cursor Cursor
Hugging Face MCP is compatible with Gemini Gemini
Hugging Face MCP is compatible with Windsurf Windsurf
Hugging Face MCP is compatible with VS Code VS Code
Hugging Face MCP is compatible with JetBrains JetBrains
Hugging Face MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Search and find models

Discover thousands of available ML models by filtering them using name, task type, framework, or author.

Inspect model files

View the exact filenames, sizes, and paths within a model repository without having to download any weights or artifacts.

Review datasets

List available datasets on the hub and view their descriptions, size details, and file trees for inspection.

Check live demos (Spaces)

Retrieve information about ML demo applications, including whether they are currently running or down.

Manage discussions

Read existing community threads for bug reports or feature requests, and also create new discussion topics on a specific model or dataset page.

Waiting for input…

AI Agent
Hugging Face

What AI agents can do with Hugging Face with 13 Tools

Use these tools to manage the full lifecycle of ML assets by listing files, creating discussions, retrieving metadata for models, and cataloging available datasets.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Hugging Face MCP

List Dataset Files

Lists all filenames within a specific Hugging Face dataset repository, helping you map out its structure.

Create Discussion

Allows you to open a brand new conversation thread on any model, dataset, or space...

Get Collection

Retrieves specific details and information for a named Hugging Face collection slug.

Get Model

Fetches core metadata about any specified model ID in the 'author/name' format.

Get Model Tags

Provides detailed tags and pipeline information for a model, showing its framework...

Get Space

Retrieves all operational details about a specific Hugging Face demo application (Space).

List Collections

Lists multiple curated model, dataset, and space collections available on the Hub.

List Datasets

Provides a list of datasets, along with their author, download counts, and creation...

List Model Discussions

Lists active discussion threads on a model page so you can review community feedback...

List Model Files

Shows the full file list, sizes, and paths for any specified model repository...

List Models

Searches and returns a list of models on the Hub based on search terms or authors.

List Spaces

Lists available demo applications (Spaces), showing their SDK, title, and author.

Get User

Checks your authenticated user account details to confirm the token is working correctly.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Hugging Face MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Hugging Face integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Hugging Face, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Hugging Face MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hugging Face. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Managed infra

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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The ML research workflow feels like constant context switching.

Today, finding a model requires a messy dance: you check Model A's card on one tab for its tags. Then, you open another tab to see if the dataset it uses is available and download its file list. Next, you jump over to a third tab just to read community discussions about potential bugs before writing any code.

With this MCP, your agent handles all that clicking. You ask one question—like 'Find me PyTorch models for image classification with good documentation'—and it pulls the tags, file structure details, and even related discussion links into a single conversation thread.

Inspect Model Artifacts Directly with list_model_files

The biggest manual headache is confirming exactly what weights or configuration files are inside a repository. You usually have to click 'Download' and then manually unzip the contents just to see if you got everything you needed.

Now, with list_model_files, your agent shows you every file name, size, and path instantly in plain text. It’s immediate validation of the entire model artifact inventory.

What Hugging Face MCP does for your AI

Connecting to the Hugging Face hub means you can treat your ML research like a natural conversation. Instead of switching tabs and manually searching across separate websites, your agent acts as an embedded data scientist. You can ask it to find models that perform specific tasks or locate datasets matching certain criteria.

The tool lets you inspect model metadata—seeing tags, download counts, and file structures—all before deciding what's useful for your project. Need to check the status of a live demo app? Just ask. If you’re working with Vinkius, this MCP makes sure that entire ecosystem of ML resources is accessible from a single point of entry, letting your AI client handle the heavy lifting.

You can even use it to create discussions or browse existing community reports, keeping all your research notes right where they belong.

Built · Hosted · Managed by Vinkius Hugging Face MCP - Discover ML Models and Datasets
Server ID 019d8446-f4c1-71a2-997f-a18c4485c0fa
Vinkius Inspector
Compliance Grade A+
Score 98.33/100
Vinkius Inspector Badge — Score 98.33/100

Frequently asked questions about Hugging Face MCP

How do I use Hugging Face MCP to find all available models? +

You can list general candidates using list_models, which lets you filter by search term or author. It returns the model ID, task tag, and download count for quick comparisons.

Can I use Hugging Face MCP to check a dataset's file structure? +

Yes, run list_dataset_files on your desired dataset repository. This gives you a clear list of every filename, like 'train.parquet', helping you understand the data layout.

What is the best way to check model tags using Hugging Face MCP? +

Use get_model_tags and provide the full author/name ID for the model. This tool gives detailed information on its framework, license, and primary task tag in one go.

How do I find live demo apps with Hugging Face MCP? +

Run list_spaces to get a catalog of all available demo applications. You can then use get_space on a specific ID to confirm its current runtime status.

Can I create discussions using the Hugging Face MCP? +

Yes, you can initiate conversations with create_discussion. Just provide the repo type (model, dataset or space), the ID, and your title to start a new thread.