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.

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Installation
Difficulty
Intermediate
Estimated Time
10-20 minutes
Requirements
Python 3.8+
FastMCP framework

Installation

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

Edit config.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