semantic-scholar-fastmcp-mcp-server
The Semantic Scholar MCP Server is an implementation of a FastMCP server that provides comprehensive access to academic paper data, author information, and citation networks. It has been refactored into a modular structure for better maintainability.
GitHub Stars
61
User Rating
Not Rated
Favorites
0
Views
35
Forks
10
Issues
4
Installation
Difficulty
IntermediateEstimated Time
10-20 minutes
Requirements
Python 3.8+FastMCP frameworkInstallation
Installation
Prerequisites
Python: 3.8 or higher
FastMCP framework
Environment variable for API key (optional)
Installation Steps
1. Clone Repository
bash
git clone https://github.com/zongmin-yu/semantic-scholar-fastmcp-mcp-server.git
cd semantic-scholar-fastmcp-mcp-server
2. Install FastMCP and Dependencies
bash
pip install fastmcp
3. Start the Server
bash
python run.py
Troubleshooting
Common Issues
Issue: Server won't start Solution: Check Python version and dependencies.Configuration
Configuration
Basic Configuration
Server Settings
Editconfig.py to set necessary configurations.
python
API_KEY = 'your-api-key'
Advanced Configuration
Environment Variables
Set the following environment variables as needed:bash
export API_KEY="your-api-key"
Security Settings
Store API keys in environment variables or secure configuration files
Set appropriate file access permissions
Examples
Examples
Basic Usage
Programmatic Usage
python
import requests
def call_mcp_tool(tool_name, params):
response = requests.post(
'http://localhost:3000/mcp/call',
json={
'tool': tool_name,
'parameters': params
}
)
return response.json()
Usage example
result = call_mcp_tool('analyze', {
'input': 'sample data',
'options': {'format': 'json'}
})
Use Cases
Search for specific papers and retrieve author information.
Explore citation networks to identify influential papers.
Perform batch retrieval of details for multiple papers.
Analyze authors' publication histories to understand research trends.
Additional Resources
Author Information
7
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35
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Total Contributions
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