A Model Context Protocol (MCP) server for analyzing academic author networks and research collaborations.

• get_coauthors: Find all co-authors for a given researcher
• get_author_keywords: Extract research keywords from Google Scholar profile

1. Clone or download this repository
2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

python server.py

result = await get_coauthors(
    name="Yann", 
    surname="LeCun",
    institution="NYU"  # Optional
)

keywords = await get_author_keywords(
    name="Yann",
    surname="LeCun"
)

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

• 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

The server includes built-in rate limiting and error handling. No additional configuration is required for basic usage.

• 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

Contributions are welcome! Please ensure all API integrations respect rate limits and terms of service.