Hf MCP
Hugging FaceOfficialPublished by Hugging Face
- Skill
- Tool integration
- Data and AI
- Apache-2.0
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The hf-mcp skill enables AI assistants to interact directly with the Hugging Face Hub. By connecting to the Hugging Face MCP server, users can search for models, datasets, research papers, and Spaces. It also provides functionality to fetch repository documentation, execute compute jobs on cloud infrastructure, and utilize Gradio Spaces as functional tools within an agentic workflow.
What it does
- Search and retrieve details for models, datasets, and research papers.
- Fetch and read repository documentation and model cards.
- Discover and invoke Gradio Spaces as functional AI tools.
- Execute and manage compute jobs on cloud GPU or CPU resources.
- Schedule recurring tasks using cron expressions.
- Access library documentation for Hugging Face tools.
When to use it
- When you need to find or compare machine learning models and datasets.
- When you want to run training or inference scripts on cloud hardware.
- When you need to integrate specific Gradio-based applications into your workflow.
- When researching the latest papers or library documentation for AI development.
- When automating data synchronization or recurring compute tasks.
Advantages
- Direct access to a vast ecosystem of models and datasets.
- Seamless transition from model discovery to execution.
- Ability to use external Gradio apps as modular tools.
- Support for both interactive and scheduled compute jobs.
Usage examples
- “Find the best model for code generation”
- The agent performs a model search filtered by task and query, then retrieves the repository details including the readme for the top result.
- “Run my training script on an A10G”
- The agent initiates a compute job on the specified hardware flavor using the provided container image and training commands.
- “Find a tool that can remove image backgrounds”
- The agent searches for relevant Gradio Spaces, views the required parameters, and invokes the space to process the image.
- “What's happening with my training job?”
- The agent queries the status of active jobs and retrieves the logs for a specific job identifier.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/huggingface/hf-mcp/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip hf-mcp.zip -d .agents/skills
Documentation by Hugging Face
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 modelsLearn 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": "$HF_TOKEN"}
})Check Job Status
User: "What's happening with my training job?"
1. hf_jobs(operation="ps")
2. hf_jobs(operation="logs", args={"job_id": "job-xxxxx"})Explore What's Trending
User: "What models are trending right now?"
model_search(sort="trendingScore", limit=20)Get Model Card Details
User: "Tell me about Mistral-7B"
hub_repo_details(repo_ids=["mistralai/Mistral-7B-v0.1"], include_readme=true)Find Quantized Models
User: "Find GGUF versions of Llama 3"
model_search(query="Llama 3 GGUF", sort="downloads", limit=10)Use a Gradio Space as a Tool
User: "Transcribe this audio file"
1. space_search(query="speech to text transcription", mcp=true)
2. dynamic_space(operation="view_parameters", space_name="openai/whisper")
3. dynamic_space(operation="invoke", space_name="openai/whisper", parameters="{\"audio\": \"...\"}")Schedule Recurring Jobs
User: "Run this data sync every day at midnight"
hf_jobs(operation="scheduled uv", args={
"script": "...",
"cron": "0 0 * * *",
"flavor": "cpu-basic"
})Tool Selection Guide
| Goal | Tool |
|---|---|
| Find models | model_search |
| Find datasets | dataset_search |
| Find Spaces/apps | space_search |
| Find papers | paper_search |
| Get repo README/details | hub_repo_details |
| Learn library usage | hf_doc_search → hf_doc_fetch |
| Run code on GPU/CPU | hf_jobs |
| Use Gradio apps as tools | dynamic_space |
| Generate images | gr1_flux1_schnell_infer or dynamic_space |
| Check auth | hf_whoami |
Tips
Use
sort="trendingScore"to find what's popular nowUse
sort="downloads"to find battle-tested optionsSet
mcp=trueinspace_searchto find Spaces usable as toolsUse
include_readme=trueinhub_repo_detailsfor full model/dataset documentationFor jobs accessing private repos, always include
secrets: {"HF_TOKEN": "$HF_TOKEN"}Use
dynamic_space(operation="discover")to see all available Space-based tasks
Files
- ATTRIBUTION.mdAdded by AutoGineer863 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md4.9 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server, Needs Python
Security
What our scanner noticed· Low risk
- Instructions that use the network
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Hugging Face
- Publisher
- Hugging Face (Official)
- Source
- huggingface/skills · hf-mcp/skills/hf-mcp · commit 25910b3
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Hugging Face or Hugging Face.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download hf-mcp.zip