A Model Context Protocol (MCP) server for analyzing academic author networks and research collaborations.
1 stars
Python
Updated Jun 18, 2025
Documentation
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\activate3. Install dependencies:
bash
pip install -r requirements.txtUsage
Running the Server
bash
python server.pyExample 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.
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