Huggingfetch

About

Huggingfetch is a powerful tool designed to significantly speed up the download of HuggingFace models by leveraging the MCP protocol. It provides seamless integration with popular AI development environments and clients such as Claude Desktop, Claude Code, Cursor, and VS Code (via the Continue plugin). Users can easily configure the tool with their HuggingFace access token and initiate model downloads directly through conversational prompts, with extensive options for filtering files, setting size limits, and specifying model revisions.

Key Features

• Flexible download options including file filtering, size limits, and revision selection
• Seamless integration with Claude Desktop/Code, Cursor, and VS Code (Continue plugin)
• Support for private models with HuggingFace access tokens
• 1 GitHub stars
• Automatic retry and resume for interrupted downloads
• Accelerated HuggingFace model downloads via MCP protocol

Use Cases

• Requesting specific AI model downloads directly from conversational interfaces.
• Managing and filtering model components for local AI development environments.
• Streamlining the acquisition of large language models for client-side applications.