# Academic Author Network MCP Server A Model Context Protocol (MCP) server for analyzing academic author networks and research collaborations. ## Features - **get_coauthors**: Find all co-authors for a given researcher - **get_author_keywords**: Extract research keywords from Google Scholar profile ## Installation 1. Clone or download this repository 2. Create a virtual environment: ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ``` 3. Install dependencies: ```bash pip install -r requirements.txt ``` ## Usage ### Running the Server ```bash python server.py ``` ### Example Tool Calls #### Finding Co-authors ```python result = await get_coauthors( name="Yann", surname="LeCun", institution="NYU" # Optional ) ``` #### Getting Research Keywords from Google Scholar ```python keywords = await get_author_keywords( name="Yann", surname="LeCun" ) ``` ## Data Sources The server uses: - **Semantic Scholar API**: Primary source for author and publication data - **OpenAlex API**: Open academic knowledge graph - **Crossref API**: DOI resolution and metadata - **Google Scholar**: Web scraping for research interests and keywords ## Features - **Rate Limiting**: Respects API rate limits and includes delays for web scraping - **Caching**: Reduces redundant API calls and scraping requests - **Error Handling**: Graceful handling of API failures and scraping issues - **Data Merging**: Combines data from multiple sources for co-authors - **Async Operations**: Parallel API requests for better performance ## Configuration The server includes built-in rate limiting and error handling. No additional configuration is required for basic usage. ## Limitations - Free tier API limits apply - Google Scholar scraping includes respectful delays - Results quality depends on author name uniqueness - Web scraping may occasionally fail due to anti-bot measures ## Contributing Contributions are welcome! Please ensure all API integrations respect rate limits and terms of service.