Frequently Asked Questions about the Semantic Scholar MCP Server

Q: What is an MCP Server? A: MCP stands for Model Context Protocol. An MCP server acts as a bridge, allowing AI models to access and interact with external data sources and tools.

Q: What is the Semantic Scholar MCP Server? A: The Semantic Scholar MCP Server is a specific MCP server that provides access to Semantic Scholar’s comprehensive database of academic research papers.

Q: What can I do with the Semantic Scholar MCP Server? A: You can use it to:

• Search for research papers using natural language queries.
• Get AI-powered recommendations for relevant papers.
• Analyze citation networks and author profiles.
• Discover content within research papers.

Q: What are the system requirements for running the server? A: You need Python 3.10 or higher, the requests, mcp, and bs4 Python packages, and a stable internet connection.

Q: How do I install the server? A: You can install it manually by cloning the repository and installing the dependencies, or use the one-click install with Smithery for supported clients.

Q: How do I configure the server for my AI client? A: The configuration process depends on the AI client you are using. Refer to the documentation for specific instructions.

Q: Can I use this server with UBOS? A: Yes! Integrating the Semantic Scholar MCP Server with UBOS significantly enhances the capabilities of AI Agents by providing access to academic knowledge.

Q: Is the Semantic Scholar MCP Server free to use? A: The server itself is open-source and free to use. However, access to the Semantic Scholar API may be subject to their terms of service.

Q: How can I contribute to the project? A: You can contribute by reporting bugs, suggesting features, submitting code, or improving the documentation. See the Contributing section of the documentation for more details.

Q: Where can I get help if I have questions or problems? A: You can ask questions on GitHub Issues or Discussions, or contact the maintainer directly.