Hugging Face
OfficialConnect to Hugging Face Hub and thousands of Gradio AI Applications
Tools (10)
hf_whoami
Hugging Face tools are being used by authenticated user 'proctorpmcp'
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.
model_search
Find Machine Learning models hosted on Hugging Face. Returns comprehensive information about matching models including downloads, likes, tags, and direct links. Include links to the models 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.
dataset_search
Find Datasets hosted on the Hugging Face hub. Returns comprehensive information about matching datasets including downloads, likes, tags, and direct links. Include links to the datasets in your response
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. You MUST consult this tool for the most up-to-date information when using Hugging Face libraries. 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.
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)