@YUZongmin
基本信息
A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"semantic-scholar-fastmcp-mcp-server": {
"command": "uvx",
"args": [
"semantic-scholar-fastmcp"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
A FastMCP server that provides comprehensive access to the Semantic Scholar API, enabling academic paper data retrieval, author information, and citation network analysis. It is intended for researchers, developers, and anyone needing programmatic access to Semantic Scholar's academic graph.
Install via pip install semantic-scholar-fastmcp or run directly with uvx semantic-scholar-fastmcp. Configure an MCP client with the uvx command and optionally set the SEMANTIC_SCHOLAR_API_KEY environment variable for higher rate limits. Once running, the server exposes 16 MCP tools for paper search, citation analysis, author queries, and recommendations.
An API key is optional. Without it, the server uses unauthenticated access with lower rate limits (100 requests per 5 minutes). With an API key, you get higher limits (1 request per second for search, batch, and recommendations; 10 per second for other endpoints).
Python 3.10 or higher.
All data is retrieved from the Semantic Scholar Academic Graph API, provided by the Allen Institute for AI (AI2).
The server uses the MCP protocol (FastMCP). Additionally, it includes an optional HTTP bridge that exposes REST endpoints on port 8000, which can be enabled via environment variables.
With an API key: search, batch, recommendation endpoints – 1 request per second; others – 10 requests per second. Without an API key: all endpoints – 100 requests per 5 minutes. These are subject to change per Semantic Scholar API terms.
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