一个用于语义学者API的FastMCP服务器实现，提供对学术论文数据、作者信息和引用网络的全面访问。

正在寻找Claude代码技能？ 看看semantic-scholar-skills——下一代工具包，捆绑了这台MCP服务器，配备了现成的Claude代码技能（/expand-references、/trace-citations]]）和Python工作流程引擎。

项目结构

该项目已被重构为模块化结构，以提高可维护性：

该结构：

• 将关注点拆分为逻辑模块
• 使代码库更易理解和维护
• 允许更好的测试和未来扩展
• 将相关功能分组
• 集中化FastMCP实例以避免循环导入

特色

• 纸质检索与发现

• 全文搜索，支持高级筛选

• 基于标题的论文匹配

• 论文推荐（单篇及多篇）

• 批量论文详细信息检索

• 带有排名策略的高级搜索

• 引用分析

• 引用网络探索

• 参考跟踪

• 引用上下文与影响分析

• 作者信息

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.

Looking for Claude Code skills? Check out semantic-scholar-skills — the next-generation toolkit that bundles this MCP server with ready-to-use Claude Code skills (/expand-references, /trace-citations, /paper-triage) and a Python workflow engine.

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