The paper introduces BioinfoMCP, a new unified platform designed to integrate complex bioinformatics tools with modern AI-agent frameworks by addressing challenges like incompatible interfaces and diverse data formats. This platform features two primary components: the BioinfoMCP Converter, which uses large language models (LLMs) to automatically generate standardized Model Context Protocol (MCP) servers from tool documentation, and the BioinfoMCP Benchmark, which systematically validates the robustness of these newly converted tools across various computational biology tasks. The conversion process is shown to be efficient, generating MCP servers for 38 tools, which enables natural-language interaction with sophisticated analyses. By standardizing communication, BioinfoMCP significantly reduces the technical barriers to AI automation in computational biology, improving expert productivity and making advanced analyses more accessible.
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