What is Hugging Face MCP?

It's an MCP (Model Context Protocol) server that connects Hugging Face to your AI, giving the agent tools to act on your data — through a single remote link.

Which AI clients does it work with?

Any MCP-compatible client: Claude (web, desktop and mobile), Cursor, ChatGPT with connectors, OpenClaw and other agents.

No. Paste the remote URL into your client, authenticate once, and you're done — no packages to install, no code to write.

Is it secure? Can the AI change my data?

Access is authorized by you and can be revoked anytime. Permissions follow what Hugging Face exposes; you approve them when connecting.

How much does it cost?

You start free and upgrade when you need more usage. Billing and limits are managed in your mcp.ai account.

Can I cancel anytime?

Yes. Plans are monthly and can be cancelled at any time, with no lock-in.

Hugging Face MCP Server and REST API

Hugging Face

Build, train and deploy state of the art models powered by the reference open source in machine learning.

클라이언트에 설치

MCP 서버 URL

https://api.mcp.ai/p_hugging_face

OAuth 2.0를 통한 보안 연결

도구 (143)

개발자용

API & 에이전트 문서

에이전트에 연결하거나 REST로 호출하기 위한 기계 판독용 문서.

Skill (사용 방법)

Markdown: MCP 또는 직접 REST API로 사용.

에이전트가 읽을 수 있는 서버 사양.

설치 프롬프트 — Claude, ChatGPT, Cursor 또는 MCP 에이전트에 붙여넣으면 알아서 연결합니다.

열기

Postman 컬렉션

REST API를 Postman으로 가져오기.

다운로드

FAQ

Hugging Face

도구 (143)

API & 에이전트 문서

자주 묻는 질문

예시 프롬프트

Hugging Face

도구 (143)

hugging_face_change_discussions_statusTool to change the status of a Hugging Face repository discussion. Use when you need to open or close discussions on models, datasets, or spaces.

hugging_face_check_dataset_validityTool to check whether a specific dataset is valid on Hugging Face Hub. Use when you need to determine what features (preview, viewer, search, filter, statistics) are available for a dataset.

hugging_face_check_models_upload_methodTool to check if files should be uploaded through the Large File mechanism or directly. Use when preparing to upload files to a Hugging Face model repository to determine the appropriate upload method

hugging_face_check_spaces_upload_methodTool to check if files should be uploaded through the Large File mechanism or directly to Hugging Face Spaces. Use when preparing to upload files to a Hugging Face Space repository to determine the ap

hugging_face_claim_settings_papers_claimTool to claim authorship of a paper on Hugging Face. Use when you need to associate yourself or another user with an ArXiv paper.

hugging_face_create_ask_accessTool to request access to a gated repository on Hugging Face Hub. Use when you need to submit an access request for models, datasets, or Spaces that require approval. The fields required vary by repos

hugging_face_create_collectionTool to create a new collection on Hugging Face. Use when you need to organize and curate models, datasets, spaces, papers, or other collections into a named collection.

hugging_face_create_datasets_branchTool to create a new branch in a Hugging Face dataset repository. Use when you need to create a branch for versioning or experimentation with dataset changes.

hugging_face_create_datasets_commitTool to create a commit in a Hugging Face dataset repository. Use when you need to add, update, or delete files in a dataset. Supports both regular files and Large File Storage (LFS) for large binary

hugging_face_create_datasets_preuploadTool to check if files should be uploaded via Large File Storage (LFS) or directly to a Hugging Face dataset repository. Use before uploading files to determine the correct upload method for each file

hugging_face_create_datasets_tagTool to create a tag on a Hugging Face dataset repository. Use when you need to mark a specific revision with a named tag.

hugging_face_create_discussionsTool to create a new discussion on a Hugging Face repository (model, dataset, or Space). Use when you need to start a conversation, report an issue, or create a pull request discussion.

hugging_face_create_discussions_commentTool to create a new comment on a Hugging Face repository discussion. Use when you need to add comments or replies to discussions on models, datasets, or spaces.

hugging_face_create_discussions_pinTool to pin or unpin a discussion on a Hugging Face repository (model, dataset, or Space). Use when you need to highlight important discussions by pinning them to the top of the list, or unpin them wh

hugging_face_create_models_branchTool to create a new branch in a Hugging Face model repository. Use when you need to create a branch for experimenting with model changes, versioning, or creating isolated development environments.

hugging_face_create_models_commitTool to create a commit to a Hugging Face model repository. Use when you need to add, update, or delete files in a model repository. Supports both standard JSON and JSON-lines (NDJSON) formats. JSON-l

hugging_face_create_models_tagTool to create a tag on a Hugging Face model repository. Use when you need to mark a specific revision with a named tag.

hugging_face_create_papers_commentTool to create a new comment on a Hugging Face paper. Use when you need to add comments or feedback to research papers on Hugging Face.

hugging_face_create_papers_comment_replyTool to create a reply to a comment on a Hugging Face paper. Use when you need to respond to an existing comment on a paper discussion.

hugging_face_create_papers_indexTool to index a paper from arXiv by its ID on Hugging Face. Use when you need to make a paper searchable and accessible on the platform. Note: If the paper is already indexed, only its authors can re-

hugging_face_create_repoTool to create a new repository (model, dataset, or Space) on Hugging Face Hub. Use when you need to initialize a new repository for uploading models, datasets, or deploying Spaces applications.

hugging_face_create_spaces_branchTool to create a new branch in a Hugging Face space repository. Use when you need to create a branch for experimenting with space changes, versioning, or creating isolated development environments.

hugging_face_create_spaces_commitTool to create a commit in a Hugging Face Space repository. Use when you need to add, update, or delete files in a Space. Supports both JSON and NDJSON (recommended) payload formats for commits.

hugging_face_create_spaces_secretsTool to create or update a secret in a Hugging Face Space. Use when you need to add or update environment variables or sensitive configuration values for a Space. This action upserts the secret, meani

hugging_face_create_spaces_tagTool to create a tag on a Hugging Face space repository. Use when you need to mark a specific revision with a named tag.

hugging_face_create_spaces_variablesTool to create or update a variable in a Hugging Face Space. Use when you need to add or update environment variables or configuration values for a Space. This action upserts the variable, meaning it

hugging_face_create_sql_console_embedTool to create a SQL Console embed for querying datasets on Hugging Face. Use when you need to create a shareable SQL query interface for exploring dataset splits. The embed allows users to execute SQ

hugging_face_create_webhookTool to create a webhook on Hugging Face that triggers on repository or discussion events. Use when you need to receive notifications for changes to specific models, datasets, or spaces.

hugging_face_delete_datasets_branchTool to delete a branch from a Hugging Face dataset repository. Use when you need to remove a branch that is no longer needed. This action permanently removes the specified branch from the dataset.

hugging_face_delete_datasets_tagTool to delete a tag from a Hugging Face dataset. Use when you need to remove a specific tag revision from a dataset repository.

hugging_face_delete_discussionsTool to delete a discussion from a Hugging Face repository. Use when you need to remove a discussion that is no longer needed. This action permanently removes the specified discussion from the reposit

hugging_face_delete_network_cidr_listTool to delete a network CIDR list entry from Hugging Face Inference Endpoints. Use when you need to remove a CIDR configuration that is no longer needed. This action permanently removes the specified

hugging_face_delete_notificationsTool to delete notifications from Hugging Face. Use when you need to remove notifications either by specific discussion IDs or by applying filters to delete multiple notifications at once. Supports ta

hugging_face_delete_settings_webhooksTool to delete a webhook from Hugging Face settings. Use when you need to remove a webhook configuration that is no longer needed.

hugging_face_delete_spaces_branchTool to delete a branch from a Hugging Face space repository. Use when you need to remove a branch that is no longer needed. This action permanently removes the specified branch from the space.

hugging_face_delete_spaces_secretsTool to delete a secret from a Hugging Face space. Use when you need to remove sensitive credentials or configuration values that are no longer needed. This action permanently removes the specified se

hugging_face_delete_spaces_tagTool to delete a tag from a Hugging Face space. Use when you need to remove a specific tag revision from a space repository.

hugging_face_delete_spaces_variablesTool to delete a variable from a Hugging Face space. Use when you need to remove configuration values or environment variables that are no longer needed. This action permanently removes the specified

hugging_face_filter_dataset_rowsTool to filter rows in a Hugging Face dataset split based on SQL-like query conditions. Use when you need to search or filter specific rows from a dataset based on column values, or to retrieve sorted

hugging_face_generate_chat_completionTool to generate a response given a list of messages in a conversational context. Supports both conversational Language Models (LLMs) and Vision-Language Models (VLMs). Compatible with OpenAI SDK.

hugging_face_generate_embeddingsTool to convert text into vector embeddings for feature extraction, semantic search, and similarity tasks. Use when you need numerical representations of text for ML applications.

hugging_face_get_daily_papersTool to retrieve daily papers from Hugging Face. Use when you need to fetch the latest AI/ML research papers shared on Hugging Face.

hugging_face_get_dataset_croissantTool to get Croissant metadata about a Hugging Face dataset. Croissant is a metadata format built on schema.org aimed at describing datasets used for machine learning. Use when you need structured met

hugging_face_get_dataset_first_rowsTool to get the first 100 rows of a dataset split along with column data types and features. Use when you need to preview or sample dataset content.

hugging_face_get_dataset_infoTool to get general information about a dataset including description, citation, homepage, license, and features (column schemas). Use when you need to understand dataset structure, available splits,

hugging_face_get_dataset_repo_infoTool to retrieve detailed information about a Hugging Face dataset repository. Use when you need metadata, card data, tags, downloads, likes, configurations, or other information about a specific data

hugging_face_get_dataset_rowsTool to retrieve a slice of rows from a Hugging Face dataset split at any given location (offset). Returns up to 100 rows at a time with complete feature type information and no truncation. Use when y

hugging_face_get_dataset_sizeTool to get the size of a Hugging Face dataset including number of rows and size in bytes. Use when you need to determine dataset size, memory requirements, or storage needs for a specific dataset.

hugging_face_get_dataset_statisticsTool to get comprehensive statistics about a dataset split including column statistics and data distribution information. Use when you need to analyze dataset composition, understand data distribution

hugging_face_get_datasets_compareTool to get a comparison (diff) between two revisions of a Hugging Face dataset. Use when you need to see what changed between dataset versions or commits.

hugging_face_get_datasets_jwtTool to generate a JWT token for accessing a Hugging Face dataset repository. Use when you need authenticated access to datasets, optionally with write access for spaces in dev mode, custom expiration

hugging_face_get_datasets_leaderboardTool to retrieve evaluation results ranked by score for a dataset's leaderboard. Use when you need to compare model performance on a specific dataset or task. Returns an array of leaderboard entries w

hugging_face_get_datasets_notebookTool to get a Jupyter notebook URL from a Hugging Face dataset repository. Use when you need to retrieve the URL for a specific .ipynb file from a dataset at a particular revision.

hugging_face_get_datasets_resolveTool to resolve and download a file from a Hugging Face dataset repository. This endpoint requires following redirections to retrieve file content or returns XET file info when Accept header is set ap

hugging_face_get_datasets_scanTool to retrieve the security scan status of a Hugging Face dataset repository. Use when you need to check for malware, pickle vulnerabilities, or other security issues in a dataset.

hugging_face_get_datasets_tags_by_typeTool to retrieve all possible tags used for datasets on Hugging Face, grouped by tag type. Use when you need to discover available dataset classification tags, filter options, or metadata categories.

hugging_face_get_datasets_treesizeTool to get the total size of a Hugging Face dataset repository at a specific revision and path. Use when you need to determine storage requirements or track repository size changes.

hugging_face_get_datasets_xet_read_tokenTool to get a read short-lived access token for XET from Hugging Face datasets. Use when you need temporary read access to dataset content through XET protocol.

hugging_face_get_discussionTool to get detailed information about a specific discussion or pull request on Hugging Face Hub. Use when you need to retrieve all comments, status changes, events, and for PRs, the diff information.

hugging_face_get_discussionsTool to retrieve discussion details from a Hugging Face repository. Use when you need to get information about a specific discussion or pull request, including comments, events, and status.

hugging_face_get_jobs_hardwareTool to retrieve available hardware configurations for Hugging Face Jobs with their specifications and pricing. Use when you need to discover compute options for running jobs.

hugging_face_get_model_infoTool to retrieve detailed information about a Hugging Face model repository. Use when you need comprehensive metadata including downloads, likes, tags, configuration, files, and more.

hugging_face_get_model_tags_by_typeTool to retrieve all possible tags used for Hugging Face models, grouped by tag type. Use when you need to discover available model tags for filtering or categorization. Optionally restrict results to

hugging_face_get_models_compareTool to compare two revisions of a Hugging Face model repository. Returns a git diff showing file changes between commits. Use when you need to see what changed between model versions.

hugging_face_get_models_jwtTool to generate a JWT token for accessing a Hugging Face model repository. Use when you need authenticated access to models, with optional write access for spaces in dev mode, custom expiration, and

hugging_face_get_models_notebookTool to retrieve a Jupyter notebook URL from a Hugging Face model repository. Use when you need to access or display a notebook file stored in a model repository.

hugging_face_get_models_scanTool to retrieve the security scan status of a Hugging Face model repository. Use when you need to check if a model has been scanned for security issues and view any detected problems.

hugging_face_get_models_treesizeTool to get the total size of a Hugging Face model repository at a specific revision and path. Use when you need to determine storage requirements or track repository size changes.

hugging_face_get_models_xet_read_tokenTool to retrieve a short-lived XET read access token for a Hugging Face model repository. Use when you need to access XET (eXtensible Tensor) data for a specific model revision.

hugging_face_get_organizations_avatarTool to retrieve the avatar URL for a Hugging Face organization. Use when you need to get the avatar image URL for a specific organization.

hugging_face_get_organizations_membersTool to retrieve a list of members for a Hugging Face organization. Use when you need to discover who belongs to an organization, with optional filtering by search terms, email, and pagination support

hugging_face_get_organizations_socialsTool to retrieve an organization's social media handles from Hugging Face. Use when you need to find an organization's GitHub, LinkedIn, or Twitter/X profiles. Only returns handles that the organizati

hugging_face_get_resolveTool to resolve a file in a Hugging Face repository. Use when you need to access files from model, dataset, or space repositories. This endpoint follows redirections (302, 307) to retrieve the actual

hugging_face_get_resolve_cache_datasetsTool to resolve a file from cache in a Hugging Face dataset repository. This endpoint follows redirections (302, 307) to retrieve file content or returns XET file info when Accept header is set approp

hugging_face_get_resolve_cache_modelsTool to resolve and retrieve files from the Hugging Face model cache. Use when you need to access model configuration files, tokenizer files, or other JSON metadata files from a specific model reposit

hugging_face_get_resolve_cache_spacesTool to resolve and retrieve a file from Hugging Face Spaces cache. Use when you need to download a file from a Space repository or get XET file information. This endpoint follows redirections (HTTP 3

hugging_face_get_settings_billing_usageTool to retrieve user billing usage for a given period from Hugging Face. Use when you need to check usage statistics, billing information, or resource consumption for the authenticated user or organi

hugging_face_get_settings_billing_usage_jobsTool to retrieve Jobs usage and billing information for the current subscription period from Hugging Face. Use when you need to check compute usage, costs, or job execution details for the authenticat