
What is academic-search-mcp-server
The academic-search-mcp-server is a specialized server developed by Afrise that leverages the Model Context Protocol (MCP) to enable seamless searching and retrieval of academic paper information from various sources. This server is designed to facilitate real-time access to academic papers' metadata, abstracts, and full-text content when available. While it is primarily optimized for integration with Anthropic's Claude Desktop client, the server's adherence to the MCP specification allows potential compatibility with other AI models and clients that support tool/function calling capabilities.
How to Use academic-search-mcp-server
To use the academic-search-mcp-server, you can follow a series of straightforward steps for installation and integration:
-
Installation: The server can be installed via the Smithery CLI or manually using the uv tool. For Smithery, execute the installation command:
npx -y @smithery/cli install @afrise/academic-search-mcp-server --client claude
For a manual setup, install dependencies, configure API keys, and run the server using:
uv add "mcp[cli]" httpx uv run server.py
-
Configuration: Integrate the server with your Claude Desktop application by adding it to your configuration file. This involves specifying the command to run the server and setting up necessary environment variables for API keys.
-
Execution: Once configured, restart your Claude Desktop to enable the server functionalities. The server will provide easy access to academic resources directly within the application.
Key Features of academic-search-mcp-server
The academic-search-mcp-server offers a suite of features tailored to enhance academic research and information retrieval:
-
Real-Time Search: Utilize the
search_papers
tool to conduct real-time searches across multiple academic sources. Input a query to receive up to ten results by default, with detailed information on each paper. -
Detailed Paper Retrieval: Access comprehensive paper information using the
fetch_paper_details
tool. You can retrieve detailed metadata, including title, authors, publication year, and more, by providing a paper identifier. -
Topic-Based Search: The
search_by_topic
tool allows users to find papers by specific topics, with optional filters for date ranges and result limits. This feature is particularly useful for narrowing down searches to relevant and timely publications. -
Structured Data Responses: The server adheres to the MCP specification, ensuring structured and consistent data responses. This includes metadata, abstracts, and potentially full-text content, enhancing the capabilities of AI clients integrating with the server.
These features make the academic-search-mcp-server a powerful resource for researchers, educators, and AI developers seeking efficient and comprehensive access to academic papers and related data.
How to Use
To use the academic-search-mcp-server, follow these steps:
- Visit https://github.com/afrise/academic-search-mcp-serverhttps://github.com/afrise...
- Follow the setup instructions to create an account (if required)
- Connect the MCP server to your Claude Desktop application
- Start using academic-search-mcp-server capabilities within your Claude conversations
Additional Information
Created
February 7, 2025
Company
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