Semantic Scholar MCP Server
A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.
What is Semantic Scholar MCP Server?
What is the Semantic Scholar MCP Server? The Semantic Scholar MCP Server is a FastMCP server implementation that provides comprehensive access to academic paper data, author information, and citation networks through the Semantic Scholar API. How to use the Semantic Scholar MCP Server? To use the server, install it using FastMCP by providing your Semantic Scholar API key (optional) and access it for various functionalities like paper search, author details, and citation analysis. Key features of the Semantic Scholar MCP Server? Paper Search & Discovery: Full-text search with advanced filtering, title-based matching, and paper recommendations. Citation Analysis: Explore citation networks and track references. Author Information: Search for authors and retrieve their publication history. Advanced Features: Complex search options, batch operations, and error handling. Use cases of the Semantic Scholar MCP Server? Conducting literature reviews through extensive paper searches. Performing citation analysis for research impact. Gathering author profiles for academic networking. Accessing batch details for multiple papers and authors efficiently. FAQ from the Semantic Scholar MCP Server? What is required to run the MCP Server? You need Python 3.8+ and the FastMCP framework installed. Is an API key necessary? No, the API key is optional. Using it grants higher rate limits and more features. What sort of data can I access? You can access paper metadata, author profiles, citation contexts, and more from the Semantic Scholar database.
As an MCP (Model Context Protocol) server, Semantic Scholar MCP Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use Semantic Scholar MCP Server
To use the server, install it using FastMCP by providing your Semantic Scholar API key (optional) and access it for various functionalities like paper search, author details, and citation analysis. Key features of the Semantic Scholar MCP Server? Paper Search & Discovery: Full-text search with advanced filtering, title-based matching, and paper recommendations. Citation Analysis: Explore citation networks and track references. Author Information: Search for authors and retrieve their publication history. Advanced Features: Complex search options, batch operations, and error handling. Use cases of the Semantic Scholar MCP Server? Conducting literature reviews through extensive paper searches. Performing citation analysis for research impact. Gathering author profiles for academic networking. Accessing batch details for multiple papers and authors efficiently. FAQ from the Semantic Scholar MCP Server? What is required to run the MCP Server? You need Python 3.8+ and the FastMCP framework installed. Is an API key necessary? No, the API key is optional. Using it grants higher rate limits and more features. What sort of data can I access? You can access paper metadata, author profiles, citation contexts, and more from the Semantic Scholar database.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like Semantic Scholar MCP Server can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like Semantic Scholar MCP Server provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.