Semantic Scholar MCP Server

A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.

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Project Structure

The project has been refactored into a modular structure for better maintainability:

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

This structure:

• Separates concerns into logical modules
• Makes the codebase easier to understand and maintain
• Allows for better testing and future extensions
• Keeps related functionality grouped together
• Centralizes the FastMCP instance to avoid circular imports

Features

• Paper Search & Discovery

  • Full-text search with advanced filtering
  • Title-based paper matching
  • Paper recommendations (single and multi-paper)
  • Batch paper details retrieval
  • Advanced search with ranking strategies

• Citation Analysis

  • Citation network exploration
  • Reference tracking
  • Citation context and influence analysis

• Author Information

  • Author search and profile details
  • Publication history
  • Batch author details retrieval

• Advanced Features

  • Complex search with multiple ranking strategies
  • Customizable field selection
  • Efficient batch operations
  • Rate limiting compliance
  • Support for both authenticated and unauthenticated access
  • Graceful shutdown and error handling
  • Connection pooling and resource management

System Requirements

• Python 3.10+
• Environment variable for API key (optional)

Installation

Quick Install (PyPI)

pip install semantic-scholar-fastmcp

Or run directly with uvx:

uvx semantic-scholar-fastmcp

MCP Client Configuration

For any MCP client that supports uvx:

{
  "mcpServers": {
    "semantic-scholar": {
      "command": "uvx",
      "args": ["semantic-scholar-fastmcp"],
      "env": {
        "SEMANTIC_SCHOLAR_API_KEY": "your-api-key-here"
      }
    }
  }
}

Installing via Smithery

To install Semantic Scholar MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install semantic-scholar-fastmcp-mcp-server --client claude

Manual Installation

1. Clone the repository:

git clone https://github.com/YUZongmin/semantic-scholar-fastmcp-mcp-server.git
cd semantic-scholar-fastmcp-mcp-server

2. Install in development mode:

pip install -e ".[dev]"

3. Run the server:

s

... [View full README on GitHub](https://github.com/zongmin-yu/semantic-scholar-fastmcp-mcp-server#readme)