The OpenAlex Author Disambiguation MCP Server is designed as an AI-friendly MCP service that uses the OpenAlex API to disambiguate authors and build comprehensive researcher profiles. It emphasizes agent-ready outputs with structured, parseable results and targeted filtering to support AI reasoning. Core capabilities include advanced author disambiguation across name variations and career transitions, institution resolution with current and past affiliations, retrieval of scholarly works (journal articles, letters, and papers), and robust citation analysis (e.g., h-index, citation counts). ORCID integration enhances identity matching accuracy, while data optimization focuses on delivering essential information for AI workflows. The server follows MCP best practices (FastMCP) with proper tool annotations, efficient HTTP client management, and rate limiting to ensure reliable client usage. Output is designed for integration with AI agents and tools (e.g., OpenAI Agents, Claude Desktop), with multiple candidate results, clean structure, and enhanced filtering options (journal-only, thresholds, temporal filters). Example tools include autocomplete_authors, search_authors, and retrieve_author_works, enabling streamlined author disambiguation and research workflow analysis.