Semantic Scholar MCP Server
by YUZongmin
# Semantic Scholar Server Refactoring
This document describes the refactoring of the Semantic Scholar server from a single monolithic file to a modular package structure.
## Motivation
The original implementation consisted of a single 2,200+ line Python file (`semantic_scholar_server.py`), which made it difficult to:
- Understand the overall structure
- Locate specific functionality
- Debug issues
- Make focused changes
- Test individual components
## Refactoring Approach
We used a modular package approach, separating concerns into logical components:
```
semantic-scholar-server/
├── semantic_scholar/ # Main package
│ ├── __init__.py # Package initialization
│ ├── server.py # Server setup and main functionality
│ ├── mcp.py # Centralized FastMCP instance definition
│ ├── config.py # Configuration classes
│ ├── utils/ # Utility modules
│ │ ├── __init__.py
│ │ ├── errors.py # Error handling
│ │ └── http.py # HTTP client and rate limiting
│ ├── api/ # API endpoints
│ ├── __init__.py
│ ├── papers.py # Paper-related endpoints
│ ├── authors.py # Author-related endpoints
│ └── recommendations.py # Recommendation endpoints
├── run.py # Entry point script
```
## Key Improvements
1. **Separation of Concerns**
- Config classes in their own module
- Utilities separated from business logic
- API endpoints grouped by domain (papers, authors, recommendations)
- Server infrastructure code isolated
- FastMCP instance centralized in its own module
2. **Improved Maintainability**
- Each file has a single responsibility
- Files are much smaller and easier to understand
- Clear imports show dependencies between modules
- Better docstrings and code organization
- No circular dependencies between modules
3. **Enhanced Extensibility**
- Adding new endpoints only requires changes to the relevant module
- Utilities can be reused across the codebase
- Configuration is centralized
- Testing individual components is much easier
- Each module imports the FastMCP instance from a central location
4. **Clearer Entry Point**
- `run.py` provides a simple way to start the server
- Server initialization is separated from the API logic
- All modules consistently import the FastMCP instance from mcp.py
## Migration Guide
The refactored code maintains the same functionality and API as the original implementation. To migrate:
1. Replace the original `semantic_scholar_server.py` with the new package structure
2. Update any import statements that referenced the original file
3. Use `run.py` as the new entry point
No changes to API usage are required - all tool functions maintain the same signatures and behavior.
## Future Improvements
The modular structure enables several future improvements:
1. **Testing**: Add unit tests for individual components
2. **Caching**: Implement caching layer for improved performance
3. **Logging**: Enhanced logging throughout the application
4. **Metrics**: Add performance monitoring
5. **Documentation**: Generate API documentation from docstrings