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Hugging Face

AI & Memory Remote Official ★ 3,871 8 tools

AI model hub for machine learning. Discover models, explore datasets, and access model documentation and capabilities.

Connect

MCP endpoint

https://huggingface.run.tools

How to connect

Smithery (hosted)

1. Open https://smithery.ai/servers/huggingface
2. Click Connect and complete OAuth in your MCP client (Claude, Cursor, VS Code, etc.)
3. MCP endpoint: https://huggingface.run.tools

Tools (8)

hf_whoami
Hugging Face tools are being used anonymously and may be rate limited. Call this tool for instructions on joining and authenticating.
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.
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 11 March 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.
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