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OpenAlex MCP Server

gpetruzella/openalex-mcp-server
0 starsUpdated 2025-11-04Community

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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Provides academic research tools via the OpenAlex API, enabling searches for papers, authors, concepts, institutions, and citation analysis.

README.md

OpenAlex MCP Server

A production-ready Model Context Protocol (MCP) server that provides academic research tools using the OpenAlex API. Built with FastAPI and designed for deployment on Google Cloud Run.

Features

🔬 Academic Research Tools

  • search_works - Search for papers, articles, and academic publications
  • search_authors - Find researchers and their profiles with h-index, citations
  • get_work_details - Get detailed metadata for specific papers
  • search_concepts - Explore research topics and their relationships
  • search_institutions - Find universities and research organizations
  • get_citations - Analyze citation networks (citing/cited works)
  • advanced_filter - Complex multi-criteria searches with OpenAlex filter syntax

🚀 MCP Protocol Features

  • Streamable-HTTP transport - Modern HTTP/SSE-based communication
  • JSON-RPC 2.0 - Standard message protocol
  • Server-Sent Events - Real-time streaming for large responses
  • Cloud-ready - Optimized for Google Cloud Run deployment

📊 OpenAlex Polite Access

  • Automatic rate limiting (10 requests/second)
  • Mailto parameter for polite pool access
  • Proper User-Agent headers
  • Exponential backoff for retries

Quick Start

Local Development

  1. Clone and setup:
cd openalex-mcp-server
cp .env.example .env
# Edit .env and set your MAILTO_EMAIL
  1. Install dependencies:
pip install -r requirements.txt
  1. Run the server:
python server.py
# Or with uvicorn:
uvicorn server:app --reload --port 8080
  1. Test the endpoint:
curl http://localhost:8080/health

Docker Local Testing

docker build -t openalex-mcp-server .
docker run -p 8080:8080 -e MAILTO_EMAIL=your-email@williamscollege.edu openalex-mcp-server

Google Cloud Run Deployment

Prerequisites

  • Google Cloud SDK installed
  • GCP project with Cloud Run API enabled
  • Docker installed locally

Deployment Steps

  1. Authenticate with Google Cloud:
gcloud auth login
gcloud config set project YOUR_PROJECT_ID
  1. Build and push container:
# Configure Docker for Google Container Registry
gcloud auth configure-docker

# Build the image
docker build -t gcr.io/YOUR_PROJECT_ID/openalex-mcp-server .

# Push to Container Registry
docker push gcr.io/YOUR_PROJECT_ID/openalex-mcp-server
  1. Deploy to Cloud Run:
gcloud run deploy openalex-mcp-server \
  --image gcr.io/YOUR_PROJECT_ID/openalex-mcp-server \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated \
  --set-env-vars MAILTO_EMAIL=your-email@williamscollege.edu \
  --memory 512Mi \
  --cpu 1 \
  --max-instances 10
  1. Get your service URL:
gcloud run services describe openalex-mcp-server --platform managed --region us-central1 --format 'value(status.url)'

Alternative: One-Command Deployment

gcloud run deploy openalex-mcp-server \
  --source . \
  --region us-central1 \
  --allow-unauthenticated \
  --set-env-vars MAILTO_EMAIL=your-email@williamscollege.edu

MCP Client Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "openalex": {
      "transport": "streamable-http",
      "url": "https://YOUR-SERVICE-URL.run.app/mcp",
      "description": "OpenAlex academic research API"
    }
  }
}

Config file locations:

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

Other MCP Clients

The server implements standard MCP over HTTP/SSE, so it works with any compatible client:

import httpx
import json

# Initialize request
init_message = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "initialize",
    "params": {
        "protocolVersion": "2025-03-26",
        "clientInfo": {
            "name": "my-client",
            "version": "1.0.0"
        }
    }
}

response = httpx.post(
    "https://YOUR-SERVICE-URL.run.app/mcp",
    json=init_message,
    headers={"Content-Type": "application/json"}
)

print(response.json())

Usage Examples

Search for Papers

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "search_works",
    "arguments": {
      "query": "machine learning climate change",
      "publication_year": "2020-2024",
      "open_access": true,
      "limit": 10
    }
  }
}

Find Researchers

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "tools/call",
  "params": {
    "name": "search_authors",
    "arguments": {
      "name": "Andrew Ng",
      "institution": "Stanford",
      "limit": 5
    }
  }
}

Get Citation Network

{
  "jsonrpc": "2.0",
  "id": 4,
  "method": "tools/call",
  "params": {
    "name": "get_citations",
    "arguments": {
      "work_id": "W2741809807",
      "direction": "citing",
      "limit": 50
    }
  }
}

Advanced Filtering

{
  "jsonrpc": "2.0",
  "id": 5,
  "method": "tools/call",
  "params": {
    "name": "advanced_filter",
    "arguments": {
      "entity_type": "works",
      "filters": {
        "publication_year": ">2020",
        "cited_by_count": ">100",
        "is_oa": true
      },
      "search": "artificial intelligence",
      "sort": "cited_by_count:desc",
      "limit": 25
    }
  }
}

API Endpoints

POST /mcp

Main MCP endpoint for JSON-RPC messages. Supports both JSON and SSE responses.

Headers:

  • Content-Type: application/json (required)
  • Accept: application/json (JSON response) or Accept: text/event-stream (SSE)

GET /mcp

Optional SSE endpoint for server-initiated messages (keepalive, notifications).

Headers:

  • Accept: text/event-stream (required)

GET /health

Health check endpoint for monitoring.

Response: {"status": "healthy", "service": "openalex-mcp-server", "version": "1.0.0"}

GET /

Service information and endpoint documentation.

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | PORT | 8080 | Server port (Cloud Run sets automatically) | | MAILTO_EMAIL | researcher@williamscollege.edu | Required for polite pool access | | OPENALEX_BASE_URL | https://api.openalex.org | OpenAlex API endpoint | | MAX_REQUESTS_PER_SECOND | 10 | Rate limit for API calls | | LOG_LEVEL | INFO | Logging verbosity | | ALLOWED_ORIGINS | None | CORS allowed origins (comma-separated) |

Architecture

openalex-mcp-server/
├── server.py              # FastAPI app with HTTP/SSE transport
├── mcp_handler.py         # MCP protocol & JSON-RPC handling
├── config.py              # Environment configuration
├── tools/
│   ├── __init__.py
│   ├── search.py          # OpenAlex API tool implementations
│   ├── filters.py         # Filter utilities
│   └── utils.py           # Formatting helpers
├── Dockerfile             # Cloud Run deployment
├── requirements.txt       # Python dependencies
├── .env.example           # Environment template
├── claude_desktop_config.json  # Client config example
└── README.md

Development

Adding New Tools

  1. Implement the tool function in tools/search.py:
async def my_new_tool(param1: str, param2: int = 10) -> str:
    """Tool description."""
    # Implementation
    return json.dumps(result)
  1. Add to MCPHandler in mcp_handler.py:
self.tools = {
    # ... existing tools
    "my_new_tool": my_new_tool,
}
  1. Add schema in _get_tool_schema():
schemas = {
    # ... existing schemas
    "my_new_tool": {
        "description": "Tool description",
        "inputSchema": {
            "type": "object",
            "properties": {
                "param1": {"type": "string", "description": "..."},
                "param2": {"type": "integer", "default": 10}
            },
            "required": ["param1"]
        }
    }
}

Running Tests

# Install test dependencies
pip install pytest pytest-asyncio httpx

# Run tests
pytest

Monitoring Cloud Run

# View logs
gcloud run services logs read openalex-mcp-server --region us-central1

# Check service status
gcloud run services describe openalex-mcp-server --region us-central1

Security Considerations

Current Configuration (Development)

  • No authentication required
  • CORS allows all origins
  • Suitable for testing and internal use

Production Hardening

  1. Enable authentication:
gcloud run deploy openalex-mcp-server \
  --no-allow-unauthenticated
  1. Set allowed origins in .env:
ALLOWED_ORIGINS=https://yourdomain.com,https://anotherdomain.com
  1. Use Cloud Run IAM for access control
  2. Enable Cloud Armor for DDoS protection
  3. Set up VPC for private networking

Rate Limiting & Polite Access

The server implements OpenAlex polite pool best practices:

  • 10 requests/second rate limit (vs 6 req/s for non-polite)
  • Mailto parameter in all requests
  • User-Agent header with contact info
  • Exponential backoff for errors
  • Response caching (where appropriate)

Always set MAILTO_EMAIL to get better rate limits!

Troubleshooting

Issue: "Origin not allowed"

Solution: Set ALLOWED_ORIGINS environment variable or update CORS middleware in server.py

Issue: Rate limiting errors

Solution: Verify MAILTO_EMAIL is set correctly for polite pool access

Issue: Cloud Run timeout

Solution: Increase timeout in deployment: ``bash gcloud run deploy openalex-mcp-server --timeout 300 ``

Issue: Memory errors

Solution: Increase memory allocation: ``bash gcloud run deploy openalex-mcp-server --memory 1Gi ``

Resources

Contributing

Contributions welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new functionality
  4. Submit a pull request

License

MIT License - See LICENSE file for details

Support

For issues and questions:

  • OpenAlex API: support@openalex.org
  • Williams College: Contact your research computing support

---

Built for Williams College undergraduate researchers 🎓

Happy researching! 🔬

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