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hf-mcp

Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.

Install / Use

npx skills add huggingface/skills --skill hf-mcp

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

93/100

Supported Platforms

Universal

Our assessment of hf-mcp

hf-mcp scores 93/100 on our quality scale, 70th of 399 Content & Media skills we index (top 18%).

Its SKILL.md is 4.8 KB long, well organised into 19 sections with 15 code examples: a solid amount of guidance for an agent.

With 11,093 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
17/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so hf-mcp is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

hf-mcp compared with similar skills

All 4 of these similar skills score higher than hf-mcp; compare them before choosing.

SkillScoreStarsUpdatedFormat
hf-mcp (this skill)by huggingface9311.1k1d agoSKILL.md
Agent-Reachby Panniantong10085.5k10d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md
rufloby ruvnet10073.3k1d agoCLAUDE.md
CowAgentby zhayujie10047.1ktodayCLAUDE.md

Frequently asked questions

How do I install hf-mcp?
Run npx skills add huggingface/skills --skill hf-mcp. The install tabs above show the steps for each supported agent.
Which AI agents does hf-mcp work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is hf-mcp safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is hf-mcp still maintained?
The repository was last updated yesterday, so hf-mcp is actively maintained.

name: hf-mcp description: Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.

Hugging Face MCP Server

Connect AI assistants to the Hugging Face Hub. Setup: https://huggingface.co/settings/mcp

Use Cases & Examples

Find the Best Model for a Task

User: "Find the best model for code generation"

1. model_search(task="text-generation", query="code", sort="trendingScore", limit=10)
2. hub_repo_details(repo_ids=["top-result-id"], include_readme=true)

Compare Models from Different Providers

User: "Compare Llama vs Qwen for text generation"

1. model_search(author="meta-llama", task="text-generation", sort="downloads", limit=5)
2. model_search(author="Qwen", task="text-generation", sort="downloads", limit=5)
3. hub_repo_details(repo_ids=["meta-llama/Llama-3.2-1B", "Qwen/Qwen3-8B"], include_readme=true)

Find Training Datasets

User: "Find datasets for sentiment analysis in English"

1. dataset_search(query="sentiment", tags=["language:en", "task_categories:text-classification"], sort="downloads")
2. hub_repo_details(repo_ids=["top-dataset-id"], repo_type="dataset", include_readme=true)

Discover AI Tools (MCP Spaces)

User: "Find a tool that can remove image backgrounds"

1. space_search(query="background removal", mcp=true)
2. dynamic_space(operation="view_parameters", space_name="result-space-id")
3. dynamic_space(operation="invoke", space_name="result-space-id", parameters="{...}")

Generate Images

User: "Create an image of a robot reading a book"

1. dynamic_space(operation="discover")  # See available tasks
2. gr1_flux1_schnell_infer(prompt="a robot sitting in a library reading a book, warm lighting, detailed")

Research a Topic

User: "What are the latest papers on RLHF?"

1. paper_search(query="reinforcement learning from human feedback", results_limit=10)
2. hub_repo_details(repo_ids=["paper-linked-model"], include_readme=true)  # If paper links to models

Learn How to Use a Library

User: "How do I fine-tune with LoRA using PEFT?"

1. hf_doc_search(query="LoRA fine-tuning", product="peft")
2. hf_doc_fetch(doc_url="https://huggingface.co/docs/peft/...")

Run a Quick GPU Job

User: "Run this Python script on a GPU"

hf_jobs(operation="uv", args={
  "script": "# /// script\n# dependencies = [\"torch\"]\n# ///\nimport torch\nprint(torch.cuda.is_available())",
  "flavor": "t4-small"
})

Train a Model on Cloud GPU

User: "Run my training script on an A10G"

hf_jobs(operation="run", args={
  "image": "pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime",
  "command": ["/bin/sh", "-lc", "pip install transformers trl && python train.py"],
  "flavor": "a10g-small",
  "secrets": {"HF_TOKEN": "$HF_TOKEN"}
})

Check Job Status

User: "What's happening with my training job?"

1. hf_jobs(operation="ps")
2. hf_jobs(operation="logs", args={"job_id": "job-xxxxx"})

Explore What's Trending

User: "What models are trending right now?"

model_search(sort="trendingScore", limit=20)

Get Model Card Details

User: "Tell me about Mistral-7B"

hub_repo_details(repo_ids=["mistralai/Mistral-7B-v0.1"], include_readme=true)

Find Quantized Models

User: "Find GGUF versions of Llama 3"

model_search(query="Llama 3 GGUF", sort="downloads", limit=10)

Use a Gradio Space as a Tool

User: "Transcribe this audio file"

1. space_search(query="speech to text transcription", mcp=true)
2. dynamic_space(operation="view_parameters", space_name="openai/whisper")
3. dynamic_space(operation="invoke", space_name="openai/whisper", parameters="{\"audio\": \"...\"}")

Schedule Recurring Jobs

User: "Run this data sync every day at midnight"

hf_jobs(operation="scheduled uv", args={
  "script": "...",
  "cron": "0 0 * * *",
  "flavor": "cpu-basic"
})

Tool Selection Guide

| Goal | Tool | |------|------| | Find models | model_search | | Find datasets | dataset_search | | Find Spaces/apps | space_search | | Find papers | paper_search | | Get repo README/details | hub_repo_details | | Learn library usage | hf_doc_search → hf_doc_fetch | | Run code on GPU/CPU | hf_jobs | | Use Gradio apps as tools | dynamic_space | | Generate images | gr1_flux1_schnell_infer or dynamic_space | | Check auth | hf_whoami |

Tips

  • Use sort="trendingScore" to find what's popular now
  • Use sort="downloads" to find battle-tested options
  • Set mcp=true in space_search to find Spaces usable as tools
  • Use include_readme=true in hub_repo_details for full model/dataset documentation
  • For jobs accessing private repos, always include secrets: {"HF_TOKEN": "$HF_TOKEN"}
  • Use dynamic_space(operation="discover") to see all available Space-based tasks

Related Skills

View on GitHub
GitHub Stars11.1k
CategoryContent
Updated1d ago
Forks749

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions