Hugging Face
AI model hub for machine learning.
Community: Submitted by a user or imported; check the owner before granting accessOnlineNo sign-inGlobalFreeRead-only
What it can do
- 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 sema
What data it sees
Do you need an account
No: the server works without sign-in
AI model hub for machine learning. Discover models, explore datasets, and access model documentation and capabilities.
Server tool list (8)
Raw names from tools/list. Only developers need these.
| 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 generation (from mcp-tools/Z-Image-Turbo) |