# Hugging Face

> Use this tool when you need to integrate thousands of machine learning models into conversation interfaces for tasks like natural language processing and image generation. It provides a simple interface to access Hugging Face models and resources, with optional authentication for both public and private resources. Ideal for workflows requiring direct machine learning capabilities, it enables easy deployment in various environments through a Docker container.

Canonical page: https://skillsregistry.net/skills/shreyaskarnik-huggingface  
JSON: https://api.skillsregistry.net/v1/skills/shreyaskarnik-huggingface

## Description

Huggingface MCP Server provides direct access to Hugging Face models and resources through a simple interface. Built by Shreyas Karnik, it leverages the huggingface-hub library to connect with the Hugging Face ecosystem, allowing AI assistants to interact with thousands of machine learning models without complex setup. The server supports optional authentication via Hugging Face API tokens, enabling access to both public and private resources. Packaged as a Docker container with Smithery.ai configuration, it's designed for easy deployment in various environments. This implementation is particularly valuable for workflows requiring natural language processing, image generation, or other machine learning capabilities directly within conversation interfaces.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/shreyaskarnik-huggingface)
- **Repository:** <https://github.com/shreyaskarnik/huggingface-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "shreyaskarnik-huggingface"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/shreyaskarnik-huggingface` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/shreyaskarnik-huggingface/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt