# 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.
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