Paper Search MCP (Node.js)

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A Node.js Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including arXiv, Web of Science, PubMed, Google Scholar, Sci-Hub, ScienceDirect, Springer, Wiley, Scopus, and 13 academic platforms in total.

✨ Key Features

🌍 13 Academic Platforms: arXiv, Web of Science, PubMed, Google Scholar, bioRxiv, medRxiv, Semantic Scholar, IACR ePrint, Sci-Hub, ScienceDirect, Springer Nature, Wiley, Scopus
🔗 MCP Protocol Integration: Seamless integration with Claude Desktop and other AI assistants
📊 Unified Data Model: Standardized paper format across all platforms
⚡ High-Performance Search: Concurrent search with intelligent rate limiting
🛡️ Type Safety: Complete TypeScript support
🎯 Academic Papers First: Smart filtering prioritizing academic papers over books
🔄 Smart Error Handling: Platform fallback and auto-retry mechanisms

📚 Supported Platforms

Platform	Search	Download	Full Text	Citations	API Key	Special Features
arXiv	✅	✅	✅	❌	❌	Physics/CS preprints
Web of Science	✅	❌	❌	✅	✅ Required	High-quality journal index
PubMed	✅	❌	❌	❌	🟡 Optional	Biomedical literature
Google Scholar	✅	❌	❌	✅	❌	Comprehensive academic search
bioRxiv	✅	✅	✅	❌	❌	Biology preprints
medRxiv	✅	✅	✅	❌	❌	Medical preprints
Semantic Scholar	✅	✅	❌	✅	🟡 Optional	AI semantic search
IACR ePrint	✅	✅	✅	❌	❌	Cryptography papers
Sci-Hub	✅	✅	❌	❌	❌	Universal paper access via DOI
ScienceDirect	✅	❌	❌	✅	✅ Required	Elsevier's full-text database
Springer Nature	✅	✅*	❌	❌	✅ Required	Dual API: Meta v2 & OpenAccess
Wiley	✅	✅	❌	❌	✅ Required	Text and Data Mining API
Scopus	✅	❌	❌	✅	✅ Required	Largest citation database

✅ Supported | ❌ Not supported | 🟡 Optional | ✅* Open Access only

🚀 Quick Start

System Requirements

Node.js >= 18.0.0
npm or yarn

Installation

# Clone repository
git clone https://github.com/your-username/paper-search-mcp-nodejs.git
cd paper-search-mcp-nodejs

# Install dependencies
npm install

# Copy environment template
cp .env.example .env

Configuration

Get Web of Science API Key
- Visit Clarivate Developer Portal
- Register and apply for Web of Science API access
- Add API key to .env file
Get PubMed API Key (Optional)
- Without API key: Free usage, 3 requests/second limit
- With API key: 10 requests/second, more stable service
- Get key: See NCBI API Keys

Configure Environment Variables

# Edit .env file
WOS_API_KEY=your_actual_api_key_here
WOS_API_VERSION=v1

# PubMed API key (optional, recommended for better performance)
PUBMED_API_KEY=your_ncbi_api_key_here

# Semantic Scholar API key (optional, increases rate limits)
SEMANTIC_SCHOLAR_API_KEY=your_semantic_scholar_api_key

# Elsevier API key (required for ScienceDirect and Scopus)
ELSEVIER_API_KEY=your_elsevier_api_key

# Springer Nature API keys (required for Springer)
SPRINGER_API_KEY=your_springer_api_key  # For Metadata API v2
# Optional: Separate key for OpenAccess API (if different from main key)
SPRINGER_OPENACCESS_API_KEY=your_openaccess_api_key

# Wiley TDM token (required for Wiley)
WILEY_TDM_TOKEN=your_wiley_tdm_token

Build and Run

Method 1: NPX (Recommended for MCP)

# Direct run with npx (most common MCP deployment)
npx -y paper-search-mcp-nodejs

# Or install globally
npm install -g paper-search-mcp-nodejs
paper-search-mcp

Method 2: Local Development

# Build TypeScript code
npm run build

# Start server
npm start

# Or run in development mode
npm run dev

MCP Server Configuration

Add the following configuration to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

NPX Configuration (Recommended)

{
  "mcpServers": {
    "paper-search-nodejs": {
      "command": "npx",
      "args": ["-y", "paper-search-mcp-nodejs"],
      "env": {
        "WOS_API_KEY": "your_web_of_science_api_key"
      }
    }
  }
}

Local Installation Configuration

{
  "mcpServers": {
    "paper_search_nodejs": {
      "command": "node",
      "args": ["/path/to/paper-search-mcp-nodejs/dist/server.js"],
      "env": {
        "WOS_API_KEY": "your_web_of_science_api_key"
      }
    }
  }
}

🛠️ MCP Tools

`search_papers`

Search academic papers across multiple platforms

// Random platform selection (default behavior)
search_papers({
  query: "machine learning",
  platform: "all",      // Randomly selects one platform for efficiency
  maxResults: 10,
  year: "2023",
  sortBy: "date"
})

// Search specific platform
search_papers({
  query: "quantum computing",
  platform: "webofscience",  // Target specific platform
  maxResults: 5
})

Platform Selection Behavior:

platform: "all" - Randomly selects one platform for efficient, focused results
Specific platform - Searches only that platform
Available platforms: arxiv, webofscience/wos, pubmed, biorxiv, medrxiv, semantic, iacr, googlescholar/scholar, scihub, sciencedirect, springer, wiley, scopus

`search_arxiv`

Search arXiv preprints specifically

search_arxiv({
  query: "transformer neural networks",
  maxResults: 10,
  category: "cs.AI",
  author: "Attention"
})

`search_webofscience`

Search Web of Science database specifically

search_webofscience({
  query: "CRISPR gene editing",
  maxResults: 15,
  year: "2022",
  journal: "Nature"
})

`search_pubmed`

Search PubMed/MEDLINE biomedical literature database

search_pubmed({
  query: "COVID-19 vaccine efficacy",
  maxResults: 20,
  year: "2023",
  author: "Smith",
  journal: "New England Journal of Medicine",
  publicationType: ["Journal Article", "Clinical Trial"]
})

`search_google_scholar`

Search Google Scholar academic database

search_google_scholar({
  query: "machine learning",
  maxResults: 10,
  yearLow: 2020,
  yearHigh: 2023,
  author: "Bengio"
})

`search_biorxiv` / `search_medrxiv`

Search biology and medical preprints

search_biorxiv({
  query: "CRISPR",
  maxResults: 15,
  days: 30
})

`search_semantic_scholar`

Search Semantic Scholar AI semantic database

search_semantic_scholar({
  query: "deep learning",
  maxResults: 10,
  fieldsOfStudy: ["Computer Science"],
  year: "2023"
})

`search_iacr`

Search IACR ePrint cryptography archive

search_iacr({
  query: "zero knowledge proof",
  maxResults: 5,
  fetchDetails: true
})

`search_scihub`

Search and download papers from Sci-Hub using DOI or paper URL

search_scihub({
  doiOrUrl: "10.1038/nature12373",
  downloadPdf: true,
  savePath: "./downloads"
})

`check_scihub_mirrors`

Check health status of Sci-Hub mirror sites

check_scihub_mirrors({
  forceCheck: true  // Force fresh health check
})

`download_paper`

Download paper PDF files

download_paper({
  paperId: "2106.12345",  // or DOI for Sci-Hub
  platform: "arxiv",      // or "scihub" for Sci-Hub downloads
  savePath: "./downloads"
})

`get_paper_by_doi`

Get paper information by DOI

get_paper_by_doi({
  doi: "10.1038/s41586-023-12345-6",
  platform: "all"
})

`get_platform_status`

Check platform status and API keys

get_platform_status({})

📊 Data Model

All platform paper data is converted to a unified format:

interface Paper {
  paperId: string;           // Unique identifier
  title: string;            // Paper title
  authors: string[];        // Author list
  abstract: string;         // Abstract
  doi: string;             // DOI
  publishedDate: Date;     // Publication date
  pdfUrl: string;          // PDF link
  url: string;             // Paper page URL
  source: string;          // Source platform
  citationCount?: number;   // Citation count
  journal?: string;         // Journal name
  year?: number;           // Publication year
  categories?: string[];    // Subject categories
  keywords?: string[];      // Keywords
  // ... more fields
}

🔧 Development

Project Structure

src/
├── models/
│   └── Paper.ts              # Paper data model
├── platforms/
│   ├── PaperSource.ts        # Abstract base class
│   ├── ArxivSearcher.ts      # arXiv searcher
│   ├── WebOfScienceSearcher.ts # Web of Science searcher
│   ├── PubMedSearcher.ts     # PubMed searcher
│   ├── GoogleScholarSearcher.ts # Google Scholar searcher
│   ├── BioRxivSearcher.ts    # bioRxiv/medRxiv searcher
|   ├── SemanticScholarSearcher.ts # Semantic Scholar searcher
|   ├── IACRSearcher.ts       # IACR ePrint searcher
|   ├── SciHubSearcher.ts     # Sci-Hub searcher with mirror management
|   ├── ScienceDirectSearcher.ts # ScienceDirect (Elsevier) searcher
│   ├── SpringerSearcher.ts   # Springer Nature searcher (Meta v2 & OpenAccess APIs)
|   ├── WileySearcher.ts      # Wiley TDM API searcher
|   └── ScopusSearcher.ts     # Scopus citation database searcher
├── utils/
│   └── RateLimiter.ts        # Token bucket rate limiter
└── server.ts                 # MCP server main file

Adding New Platforms

Create new searcher class extending PaperSource
Implement required abstract methods
Register new searcher in server.ts
Add corresponding MCP tool

Testing

# Run tests
npm test

# Run linting
npm run lint

# Code formatting
npm run format

🌟 Platform-Specific Features

Springer Nature Dual API System

Springer Nature provides two APIs:

Metadata API v2 (Main API)
- Endpoint: https://api.springernature.com/meta/v2/json
- Searches all Springer content (subscription + open access)
- Requires API key from https://dev.springernature.com/
OpenAccess API (Optional)
- Endpoint: https://api.springernature.com/openaccess/json
- Only searches open access content
- May require separate API key or special permissions
- Better for finding downloadable PDFs

// Search all Springer content
search_springer({
  query: "machine learning",
  maxResults: 10
})

// Search only open access papers
search_springer({
  query: "COVID-19",
  openAccess: true,  // Uses OpenAccess API if available
  maxResults: 5
})

Web of Science Advanced Search

// Use Web of Science query syntax
search_webofscience({
  query: 'TS="machine learning" AND PY=2023',
  maxResults: 20
})

// Author search
search_webofscience({
  query: 'AU="Smith, J*"',
  maxResults: 10
})

// Journal search
search_webofscience({
  query: 'SO="Nature" AND PY=2022-2023',
  maxResults: 15
})

Supported Fields:

TS: Topic search
AU: Author
SO: Source journal
PY: Publication year
DO: DOI
TI: Title

Google Scholar Features

Academic Paper Priority: Automatically filters out books, prioritizes peer-reviewed papers
Citation Data: Provides citation counts and academic metrics
Anti-Detection: Smart request patterns to avoid blocking
Comprehensive Coverage: Searches across all academic publishers

Semantic Scholar Features

AI-Powered Search: Semantic understanding of queries
Citation Networks: Paper relationships and influence metrics
Open Access PDFs: Direct links to freely available papers
Research Fields: Filter by specific academic disciplines

Sci-Hub Features

Universal Access: Access papers using DOI or direct URLs
Mirror Network: Automatic detection and use of fastest available mirror (11+ mirrors)
Health Monitoring: Continuous monitoring of mirror site availability
Automatic Failover: Seamless switching between mirrors when one fails
Smart Retry: Automatic retry with different mirrors on failure
Response Time Optimization: Mirrors sorted by response time for best performance

📝 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

Fork the project
Create feature branch (git checkout -b feature/amazing-feature)
Commit changes (git commit -m 'Add amazing feature')
Push to branch (git push origin feature/amazing-feature)
Open Pull Request

🐛 Issue Reporting

If you encounter issues, please report them at GitHub Issues.

🙏 Acknowledgments

Original paper-search-mcp for the foundation
MCP community for the protocol standards

⭐ If this project helps you, please give it a star!