Integrates Hugging Face Hub resources as AI tools for model discovery and dataset retrieval.
Install
mkdir -p .claude/skills/hf-mcp && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8795" && unzip -o skill.zip -d .claude/skills/hf-mcp && rm skill.zipInstalls to .claude/skills/hf-mcp
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Query Hugging Face repositories for model metadata and readme files
- →Sort and filter datasets based on tasks, language, and download counts
- →Invoke Gradio Space tools directly for image generation or analysis
- →Extract citations and linked repository data from research papers
How it works
Queries the Hugging Face API via the MCP protocol to fetch registry data and execute remote Gradio API calls.
Inputs & outputs
When to use hf-mcp
- →Find code generation models
- →Compare model performance
- →Download training datasets
About this skill
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": "$HF_TOKEN"}
})
Check Job Status
User: "What's happening with my training job?"
1. hf_jobs(operation="ps")
2. hf_jobs(operation="logs", args={"job_id": "job-xxxxx"})
Explore What's Trending
User: "What models are trending right now?"
model_search(sort="trendingScore", limit=20)
Get Model Card Details
User: "Tell me about Mistral-7B"
hub_repo_details(repo_ids=["mistralai/Mistral-7B-v0.1"], include_readme=true)
Find Quantized Models
User: "Find GGUF versions of Llama 3"
model_search(query="Llama 3 GGUF", sort="downloads", limit=10)
Use a Gradio Space as a Tool
User: "Transcribe this audio file"
1. space_search(query="speech to text transcription", mcp=true)
2. dynamic_space(operation="view_parameters", space_name="openai/whisper")
3. dynamic_space(operation="invoke", space_name="openai/whisper", parameters="{\"audio\": \"...\"}")
Schedule Recurring Jobs
User: "Run this data sync every day at midnight"
hf_jobs(operation="scheduled uv", args={
"script": "...",
"cron": "0 0 * * *",
"flavor": "cpu-basic"
})
Tool Selection Guide
| Goal | Tool |
|---|---|
| Find models | model_search |
| Find datasets | dataset_search |
| Find Spaces/apps | space_search |
| Find papers | paper_search |
| Get repo README/details | hub_repo_details |
| Learn library usage | hf_doc_search → hf_doc_fetch |
| Run code on GPU/CPU | hf_jobs |
| Use Gradio apps as tools | dynamic_space |
| Generate images | gr1_flux1_schnell_infer or dynamic_space |
| Check auth | hf_whoami |
Tips
- Use
sort="trendingScore"to find what's popular now - Use
sort="downloads"to find battle-tested options - Set
mcp=trueinspace_searchto find Spaces usable as tools - Use
include_readme=trueinhub_repo_detailsfor full model/dataset documentation - For jobs accessing private repos, always include
secrets: {"HF_TOKEN": "$HF_TOKEN"} - Use
dynamic_space(operation="discover")to see all available Space-based tasks
When not to use it
- →Accessing private datasets without proper authentication tokens
- →Performing heavy training or fine-tuning workloads locally
Prerequisites
Limitations
- →Limited by the exposed functionality of specific Gradio Spaces
- →Dependent on stable network connectivity to the Hugging Face Hub
How it compares
It bridges the gap between static browsing and direct tool interaction with hosted AI research artifacts.
Compared to similar skills
hf-mcp side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| hf-mcp (this skill) | 0 | 7mo | No flags | Intermediate |
| qiskit | 4 | 7mo | Review | Advanced |
| pennylane | 1 | 7mo | Review | Advanced |
| model-registry-maintainer | 0 | 8mo | Caution | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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