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MCP connect URL: https://huggingface.co/mcp
Skill page: https://www.mcpbundles.com/skills/huggingface-mcp
Publisher MCP server
Tools: 10
Live probe refreshed Nov 11, 2026 · Endpoint host huggingface.co
Explore capabilities (10)
read 7
write 1
other 2
Hf
4
Hub Repo
2
Other capabilities
4
Hf Whoami
read
hf_whoami
Hugging Face tools are being used by authenticated user 'ozboytr'
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HuggingFace
Connect your account, then chat with AI to run tools.
Hugging Face is an AI and machine learning platform that provides access to thousands of pre-trained models, datasets, and tools for natural language processing, computer vision, and other AI tasks. It offers model hosting, inference APIs, and collaborative ML development tools.
This listing identifies a third-party MCP server. MCPBundles is not affiliated with, sponsored by, or endorsed by the service or its operator unless stated on this page.
Hf Whoami — Hugging Face tools are being used by authenticated user 'ozboytr'
Space Search — Find Hugging Face Spaces using semantic search. IMPORTANT Only MCP Servers can be used with the dynamic_space toolInclude links to the Space when presenting the results.
Hub Repo Search — Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Use space_search for semantic-first discovery of Spaces. Include links to repositories in your response.
Paper Search — Find Machine Learning research papers on the Hugging Face hub. Include 'Link to paper' When presenting the results. Consider whether tabulating results matches user intent.
Hub Repo Details — Get details for one or more Hugging Face repos (model, dataset, or space). Auto-detects type unless specified. For datasets, use operations: overview, dataset_structure, dataset_preview. Use dataset_structure first to discover configs, splits, sizes, and schema. Use dataset_preview only when config and split are known, unless the dataset has a single config/split.
Hf Doc Search — Search and Discover Hugging Face Product and Library documentation. Send an empty query to discover structure and navigation instructions. Knowledge up-to-date as at 4 June 2026. Combine with the Product filter to focus results.
Hf Doc Fetch — Fetch a document from the Hugging Face or Gradio documentation library. For large documents, use offset to get subsequent chunks.
Dynamic Space — Perform Tasks with Hugging Face Spaces. Use "discover" to view available Tasks. Examples are Image Generation/Editing, Background Removal, Text to Speech, OCR and many more. Call with no arguments for full usage instructions.
hf_hub_query - hf_hub_query
Frequently Asked Questions
What is the HuggingFace MCP server?
Hugging Face is an AI and machine learning platform that provides access to thousands of pre-trained models, datasets, and tools for natural language processing, computer vision, and other AI tasks. It offers model hosting, inference APIs, and collaborative ML development tools. It provides MCP tools that your client discovers when it connects (this page may not list every tool name) that AI agents can use through the Model Context Protocol (MCP).
How do I connect HuggingFace to my AI agent?
Add the MCPBundles server URL to your MCP client configuration (Claude Desktop, Cursor, VS Code, etc.). The URL format is: https://mcp.mcpbundles.com/bundle/huggingface-mcp. Authentication is handled automatically.
Remote MCP directoryUnlimited tool calls through MCPBundlesThe operator of this MCP may charge for API usage, seats, or OAuth access. Check their site before heavy use.
— Read-only Hugging Face Hub navigator for discovery, lookup, filtering, ranking, counts, field-constrained extraction, and relationship questions across users, orgs, models, datasets, spaces, collections, discussions, daily papers, recent activity, followers/following, likes, and likers. Good for structured raw outputs and compact results. Generated helper calls can explicitly bound limit, scan_limit, max_pages, and ranking_window for brevity or broader coverage, and the tool can also be asked ab
Gr1 Z Image Turbo Generate — Generate an image using the Z-Image model based on the provided prompt and settings. This function is triggered when the user clicks the "Generate" button. It processes the input prompt (optionally enhancing it), configures generation parameters, and produces an image using the Z-Image diffusion transformer pipeline. Returns: tuple: (gallery_images, seed_str, seed_int), - seed_str: String representation of the seed used for generation, - seed_int: Integer representation of the seed used for gene
HuggingFace is a remote MCP server. The live tool list is supplied by the server when your MCP client connects, so the count is not fixed on this public page. After you connect in MCPBundles Studio or your client, you will see the tools your session can call.
What authentication does HuggingFace require?
HuggingFace uses One-click sign in. HuggingFace requires credentials. Connect via MCPBundles and authentication is handled automatically.
MCPBundles is an independent platform built on the open Model Context Protocol standard. MCPBundles is not affiliated with, sponsored by, or endorsed by Anthropic PBC.
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