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/hf-mcp

@fa7188e official
by Hugging Facehuggingface/skills11k stars
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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.

Use this Skill: https://skilld.dev/gh/huggingface/skills/hf-mcp

This session only. Nothing lands on disk.

SKILL.md

≈58 tokens always: the name and description. ≈1.2k when used: this file.

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

Source: SKILL.md on GitHub

1 warning4d3 checks · Risk SAFE
  • Gen Agent Trust Hub4d

    This skill provides a robust interface for interacting with the Hugging Face Hub, offering capabilities for research, tool discovery, and compute job management. It includes security considerations such as remote code execution for compute tasks and the processing of external repository documentation, which are standard for its intended use as a machine learning development tool. Users should review the specific scripts and data processed through these interfaces.

  • Socket4d

    No alerts

  • Snyk4d

    Risk: MEDIUM · 1 issue

Signed by skilld at fa7188e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Activeupdated 9 months ago
  • MCP
  • huggingface
  • model-search
  • datasets
  • spaces
  • gradio
  • gpu-jobs
  • papers
  • inference

README badge

README badge for huggingface/skills/hf-mcp

Exposes Hugging Face Hub search and compute via MCP tools. Search models, datasets, Spaces, and papers; fetch repo details and documentation; run Python scripts or training jobs on Hugging Face GPU infrastructure; invoke Gradio Spaces as callable tools. Requires connection to the HF MCP server.

Generated from the current SKILL.md.

What Hugging Face Hub resources can this skill search and access?
The skill searches models, datasets, Spaces, and papers on Hugging Face Hub. It can fetch repository details including READMEs, access Hugging Face library documentation, and invoke Gradio Spaces as tools.
Can I run training jobs or scripts on GPU with this skill?
Yes. The hf_jobs tool runs Python scripts or Docker containers on Hugging Face compute flavors (CPU, T4, A10G, etc.) and supports scheduled recurring jobs via cron expressions.
What do I need to set up to use this skill?
You must connect to the Hugging Face MCP server. Setup instructions are at https://huggingface.co/settings/mcp.
Can I use Gradio Spaces as tools in my workflows?
Yes. The skill can search for Spaces marked with mcp=true, view their parameters, and invoke them with custom inputs—effectively turning Gradio apps into callable tools.
How do I authenticate when accessing private repositories or running jobs?
Pass your Hugging Face token via the secrets parameter in hf_jobs operations: `secrets: {"HF_TOKEN": "$HF_TOKEN"}`.

Generated from the current SKILL.md. These answers refresh after source changes.