# MCP HuggingFetch

> Use this tool when you need to download HuggingFace models efficiently using natural language requests. It solves problems of model accessibility and management by allowing file filtering, size limits, and custom download directories. Ideal for AI development environments like Claude Desktop, VS Code, and Cursor, where seamless model integration is crucial.

Canonical page: https://skillsregistry.net/skills/freefish1218-mcp-huggingfetch  
JSON: https://api.skillsregistry.net/v1/skills/freefish1218-mcp-huggingfetch

## Description

Enables users to download HuggingFace models through natural language requests with support for file filtering, size limits, and custom download directories. Supports various AI development environments including Claude Desktop, VS Code, and Cursor.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-04-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mcvx5mcjci)
- **Repository:** <https://github.com/freefish1218/mcp-huggingfetch>

## 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": "freefish1218-mcp-huggingfetch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/freefish1218-mcp-huggingfetch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/freefish1218-mcp-huggingfetch/pull`

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