hf-trending-mcp
HF Trending MCP 服务器
一个跟踪Hugging Face上趋势模型、数据集和空间的 MCP 服务器。
它提供工具和提示来获取热门内容、搜索特定项目并分析当前趋势,使其成为开发人员、研究人员和人工智能爱好者的宝贵工具。
特征
趋势工具:检索具有可自定义限制的顶级趋势模型、数据集和空间。
搜索功能:通过跨模型、数据集或空间的查询搜索趋势项目。
趋势分析提示:内置提示,用于分析和总结 Hugging Face 上的当前趋势。
Related MCP server: Hugging Face MCP Server
安装
设置
克隆存储库:
git clone https://github.com/kukapay/hf-trending-mcp.git cd hf-trending-mcp安装依赖项:
pip install mcp[cli] httpx客户端配置:
"mcpServers": { "hf-trending-mcp": { "command": "python", "args": [ "path/to/hf-trending-mcp/main.py" ] } }
用法
服务器运行或安装完成后,您可以使用 MCP 客户端(例如 Claude Desktop)与其交互。以下是一些示例提示:
获取热门内容
输入:
“向我展示 Hugging Face 上最流行的 5 个模特。”
输出:
google/vit-base-patch16-224 (Downloads: 12345, Likes: 678)
Tags: vision, transformer
facebook/detr-resnet-50 (Downloads: 9876, Likes: 543)
Tags: object-detection, transformer
...输入:
“目前最流行的 10 个数据集是什么?”
输出:
imdb (Downloads: 45678, Likes: 2345)
Tags: nlp, sentiment-analysis
squad (Downloads: 34567, Likes: 1987)
Tags: nlp, question-answering
...输入:
“列出最热门的 3 个空间。”
输出:
gradio/image-classifier (Likes: 890, SDK: Gradio)
Tags: demo, vision
streamlit/text-generator (Likes: 765, SDK: Streamlit)
Tags: nlp, demo
...搜索热门商品
输入:
“搜索流行的 NLP 模型,限制为 5 个。”
输出:
bert-base-uncased (Likes: 456)
Tags: nlp, transformer
distilbert-base-uncased (Likes: 321)
Tags: nlp, transformer
...输入:
“查找有关计算机视觉的趋势数据集。”
输出:
coco (Likes: 1234)
Tags: computer-vision, object-detection
imagenet-1k (Likes: 987)
Tags: computer-vision, classification
...分析趋势
输入:
“分析一下Hugging Face目前的流行趋势。”
输出:
结合所有趋势工具的结果,给出详细的响应,然后进行分析(由客户的 AI 生成):
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 详细信息
工具
get_trending_models(limit: int = 10):获取具有下载、喜欢和标签的流行模型。get_trending_datasets(limit: int = 10):获取具有下载、喜欢和标签的趋势数据集。get_trending_spaces(limit: int = 10):获取具有点赞、SDK 信息和标签的热门空间。search_trending(query: str, type: str = "models", limit: int = 10):按查询和类型搜索趋势项目。
迅速的
analyze_trends():通过结构化的提示指导对趋势项目的分析。
执照
本项目遵循 MIT 许可证。详情请参阅LICENSE文件。
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