Hugging Face MCP Server

Inspect the current Hugging Face authentication context, including the account, visible organization memberships, and credential access details. Read-only and never returns credential values.

Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Include links to repositories in your response.

Create a Hugging Face model, dataset, Space, or bucket repository using an hf:// destination URI. Set source_uri to duplicate an existing model, dataset, or Space server-side.

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.

Use to access the Hugging Face Hub. Navigate resources with ls, cat, find, stat, and search over hf:// URIs. Roots: hf://models, hf://datasets, hf://spaces, hf://buckets, hf://collections, hf://papers, hf://docs. For papers, ls hf://papers/ARXIV_ID to discover related resources; cat hf://papers/ARXIV_ID/paper.md or metadata.json. Documentation paths include the current version from each product's llms.txt manifest. Grammar; each token below is one args array element: ls URI [(-R|-r|-lR|-laR|--recursive)] [(-l|-a|-la|-al|--long)] [--glob GLOB] [(-type|--type|--entry-type) TYPE] [--sort SORT] [(-limit|--limit) N] cat URI [RELATIVE_PATH] [(-offset|--offset) N] [(-max-bytes|--max-bytes) N] stat URI [RELATIVE_PATH] find URI [(-R|-r|--recursive)] [(-name|--name|--glob) GLOB] [(-path|--path) GLOB] [(-type|--type|--entry-type) TYPE] [(-limit|--limit) N] search URI [QUERY...] [(-type|--type|--entry-type) TYPE] [--sort SORT] [--tag TAG] [--kind mcp] [(-limit|--limit) N] TYPE = file|dir|repo|bucket|collection|paper|link. Type aliases: f=file, d=dir, l=link, model|dataset|space=repo. SORT = createdAt|downloads|likes|lastModified|likes30d|trendingScore|mainSize|id|trending|upvotes. URI uses hf://, a typed shorthand such as models/OWNER/REPO, or a canonical https://huggingface.co URL. QUERY and GLOB are each one string token. Search URI: hf://models|datasets|spaces[/OWNER], hf://collections[/OWNER], any hf://docs scope, or exactly hf://papers; not hf://. Repository and collection searches may omit QUERY to browse or filter; documentation and paper searches require it. Search joins multiple positional QUERY tokens with spaces. Cat and stat join one RELATIVE_PATH token to URI. Long-list flags are accepted for compatibility; hf_fs listings are already structured, so they do not alter output. Find is already recursive, so recursive flags are accepted without altering behavior. Space search: hf://spaces uses semantic search; repeat --tag to require tags, or use --kind mcp for --tag mcp-server. hf://spaces/OWNER uses owner-scoped keyword search. Documentation: ls hf://docs for products; search any docs scope; use returned hf:// URIs verbatim. Trending listings: ls hf://models/trending, hf://datasets/trending, or hf://spaces/trending. They return up to 20 entries. Trending paths imply trending order; --sort trending|trendingScore is redundant but valid. Trending papers: ls hf://papers/trending. TYPE filters mixed results; omit it when the URI already fixes the result type. Limits and path-specific behavior are documented at hf://README.md. Omit --limit and --sort unless the request asks for a cap, ordering, or exhaustive results. No pipes, redirects, shell expansion, or multiple commands.

Remote compute for Hugging Face workflows. Run Python/UV or Docker jobs to deeply analyze Hub datasets, repos, traces, models, and large files; compute trends/statistics; run batch inference/evaluation; or perform long-running work with installed libraries. Use for dataset/repo analysis prompts when local chat inspection is insufficient. Includes submit, logs, inspect, cancel, schedule, and volume mounting.

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.

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)