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hf-trending-mcp

by kukapay
GitHub
Python
MIT License
1
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An MCP server that tracks trending models, datasets, and spaces on Hugging Face.

It provides tools and prompts to fetch trending content, search for specific items, and analyze current trends, making it a valuable tool for developers, researchers, and AI enthusiasts.

License Python Status

Features

  • Trending Tools: Retrieve the top trending models, datasets, and spaces with customizable limits.
  • Search Functionality: Search trending items by query across models, datasets, or spaces.
  • Trend Analysis Prompt: A built-in prompt to analyze and summarize current trends on Hugging Face.

Installation

Setup

  1. Clone the Repository:
    git clone https://github.com/kukapay/hf-trending-mcp.git cd hf-trending-mcp
  2. Install Dependencies:
    pip install mcp[cli] httpx
  3. Client Configuration:
    "mcpServers": { "hf-trending-mcp": { "command": "python", "args": [ "path/to/hf-trending-mcp/main.py" ] } }

Usage

Once the server is running or installed, you can interact with it using an MCP client (e.g., Claude Desktop). Below are some example prompts:

Fetch Trending Content

Input:

"Show me the top 5 trending models on Hugging Face."

Output:

google/vit-base-patch16-224 (Downloads: 12345, Likes: 678) Tags: vision, transformer facebook/detr-resnet-50 (Downloads: 9876, Likes: 543) Tags: object-detection, transformer ...

Input:

"What are the top 10 trending datasets right now?"

Output:

imdb (Downloads: 45678, Likes: 2345) Tags: nlp, sentiment-analysis squad (Downloads: 34567, Likes: 1987) Tags: nlp, question-answering ...

Input:

"List the top 3 trending spaces."

Output:

gradio/image-classifier (Likes: 890, SDK: Gradio) Tags: demo, vision streamlit/text-generator (Likes: 765, SDK: Streamlit) Tags: nlp, demo ...

Input:

"Search for trending NLP models, limit to 5."

Output:

bert-base-uncased (Likes: 456) Tags: nlp, transformer distilbert-base-uncased (Likes: 321) Tags: nlp, transformer ...

Input:

"Find trending datasets about computer vision."

Output:

coco (Likes: 1234) Tags: computer-vision, object-detection imagenet-1k (Likes: 987) Tags: computer-vision, classification ...

Input:

"Analyze the current trends on Hugging Face."

Output:

A detailed response combining results from all trending tools, followed by an analysis (generated by the client’s AI):

Top Trending Models: google/vit-base-patch16-224 (Downloads: 12345, Likes: 678) Tags: vision, transformer ... Top Trending Datasets: imdb (Downloads: 45678, Likes: 2345) Tags: nlp, sentiment-analysis ... Top Trending Spaces: gradio/image-classifier (Likes: 890, SDK: Gradio) Tags: demo, vision ... Summary: Vision models like ViT are trending, likely due to recent advancements in image processing. NLP datasets remain popular for text-based AI research, and Gradio spaces are gaining traction for interactive demos.

API Details

Tools

  • get_trending_models(limit: int = 10): Fetches trending models with downloads, likes, and tags.
  • get_trending_datasets(limit: int = 10): Fetches trending datasets with downloads, likes, and tags.
  • get_trending_spaces(limit: int = 10): Fetches trending spaces with likes, SDK info, and tags.
  • search_trending(query: str, type: str = "models", limit: int = 10): Searches trending items by query and type.

Prompt

  • analyze_trends(): Guides the analysis of trending items with a structured prompt.

License

This project is licensed under the MIT License. See the LICENSE file for details.

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

An MCP server that tracks trending AI models, datasets, and spaces on Hugging Face.

  1. Features
    1. Installation
      1. Setup
    2. Usage
      1. Fetch Trending Content
      2. Search Trending Items
      3. Analyze Trends
    3. API Details
      1. Tools
      2. Prompt
    4. License

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