What dependencies does Open Alex MCP require?
Python 3.10 or higher and an MCP‑compatible client (e.g., Claude Desktop). The package uses the OpenAlex API and the FastMCP framework.
Open Alex MCP Server
@drAbreu
基本信息
关于 Open Alex MCP Server
Professional MCP server for OpenAlex academic research - ML-powered author disambiguation, institution resolution, and comprehensive researcher profiles with ORCID integration
Open Alex MCP Server 配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"alex-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/drAbreu/alex-mcp.git",
"alex-mcp"
]
}
}
}Open Alex MCP Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
概览
What is Open Alex MCP?
It is a professional Model Context Protocol (MCP) server for author disambiguation and institution resolution using the OpenAlex.org API. It provides tools for author search, work discovery, topic analysis, and source lookup, targeting researchers, librarians, and AI agents.
How to use Open Alex MCP?
Install Python 3.10+, clone the repository, create a virtual environment, and install the package with pip install -e .. Run the server with ./run_alex_mcp.sh. Configure an MCP-compatible client (e.g., Claude Desktop) by adding a JSON entry pointing command to the script. The server exposes tools such as disambiguate_author, search_authors, get_author_profile, resolve_institution, search_works, get_work_details, search_topics, analyze_topics, and search_sources.
Key features of Open Alex MCP
- ML-powered author disambiguation with confidence scoring
- Institution name and abbreviation resolution
- ORCID integration for highest‑accuracy matching
- Career stage determination and metrics
- Multiple ranked candidates for automated decision‑making
- Built with FastMCP following MCP best practices
Use cases of Open Alex MCP
- Disambiguating an author’s identity when multiple researchers share a name
- Expanding institutional abbreviations (e.g., MIT → Massachusetts Institute of Technology)
- Searching scholarly works with filters by author, year, source type, or topic
- Retrieving detailed profiles and publication lists for a specific author
- Analyzing a text’s title/abstract to identify research topics and concepts
常见问题
Where does the data come from?
All data is retrieved in real‑time from the OpenAlex.org API. No local database or API key is mentioned.
What are the known limits?
The server implements respectful API usage with proper delays and rate limiting. Tool parameters have maximum result limits (e.g., `max_candidates` between 1–25).
Do I need an API key?
No. The README does not mention any authentication or API key requirement for accessing OpenAlex.
Which transport protocol does it use?
It uses the Model Context Protocol (MCP). The specific transport (stdio, HTTP, etc.) is not detailed in the README.
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