HF Trending

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

python

3

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "kukapay-hf-trending-mcp": {
      "command": "python",
      "args": [
        "path/to/hf-trending-mcp/main.py"
      ]
    }
  }
}

You can run the HF Trending MCP Server to fetch and analyze trending Hugging Face models, datasets, and spaces. It exposes simple MCP commands to retrieve top items, search by query, and analyze current trends, making it easy to build dashboards, prompts, or automation around what’s popular in the Hugging Face ecosystem.

How to use

Interact with this MCP server using an MCP client to fetch, search, and analyze trending content. You can request the top trending models, datasets, and spaces, search by a keyword across categories, and generate a summarized trend analysis. Use natural language prompts like those shown in usage examples to guide the responses from the client.

How to install

Prerequisites: you need Python and pip installed on your system.

Step 1: Clone the repository and navigate into the project directory.

git clone https://github.com/kukapay/hf-trending-mcp.git
cd hf-trending-mcp

Step 2: Install the required Python dependencies, including MCP tooling and HTTP client support.

pip install mcp[cli] httpx

Step 3: Configure the MCP client to connect to your local server using the provided command.

"mcpServers": { 
  "hf_trending_mcp": { 
    "command": "python", 
    "args": [ "path/to/hf-trending-mcp/main.py" ]
  } 
}

Additional setup notes

The server is designed to run locally via a Python script. Ensure your Python environment has access to the dependencies listed above. You can adjust the path in the client configuration to point to the actual location of main.py within your clone.

Configuration and usage notes

Configuration focuses on how you connect your MCP client to the local Python runner. The following MCP server entry should be used by your client to start the local server process.

{
  "mcpServers": {
    "hf_trending_mcp": {
      "command": "python",
      "args": [ "path/to/hf-trending-mcp/main.py" ]
    }
  }
}

Examples and prompts you can use

Fetch Trending Content: "Show me the top 5 trending models on Hugging Face."

Search Trending Items: "Search for trending NLP models, limit to 5."

Analyze Trends: "Analyze the current trends on Hugging Face."

Security and maintenance

Keep your dependencies up to date and limit exposure of the local MCP runner if you are exposing it beyond your local environment. Use standard security practices for Python applications, such as virtual environments and regular dependency updates.

Troubleshooting

If the MCP client cannot start the server, verify that Python is installed and the path to main.py is correct. Ensure you have network access for any additional toolchains your prompts may rely on during execution.

Available tools

get_trending_models

Fetches top trending models with downloads, likes, and tags.

get_trending_datasets

Fetches top trending datasets with downloads, likes, and tags.

get_trending_spaces

Fetches top trending spaces with likes, SDK info, and tags.

search_trending

Searches trending items by query and type (models, datasets, or spaces) with a limit.

analyze_trends

Guides the analysis of trending items with a structured prompt to summarize trends.