Bioinformatics tools are essential for complex computational biology tasks, yet their integration with emerging AI-agent frameworks is hindered by incompatible interfaces, heterogeneous input-output formats, and inconsistent parameter conventions. The Model Context Protocol (MCP) provides a standardized framework for tool-AI communication, but manually converting hundreds of existing and rapidly growing specialized bioinformatics tools into MCP-compliant servers is labor-intensive and unsustainable. Here, we present BioinfoMCP, a unified platform comprising two components: BioinfoMCP Converter, which automatically generates robust MCP servers from tool documentation using large language models, and BioinfoMCP Benchmark, which systematically validates the reliability and versatility of converted tools across diverse computational tasks. We present a platform of 38 MCP-converted bioinformatics tools, extensively validated to show that 94.7% successfully executed complex workflows across three widely used AI-agent platforms. By removing technical barriers to AI automation, BioinfoMCP enables natural-language interaction with sophisticated bioinformatics analyses without requiring extensive programming expertise, offering a scalable path to intelligent, interoperable computational biology.

翻译：生物信息学工具对于复杂的计算生物学任务至关重要，然而，它们与新兴AI智能体框架的集成却因接口不兼容、输入输出格式异构以及参数约定不一致而受阻。模型上下文协议（MCP）为工具与AI之间的通信提供了一个标准化框架，但将数百个现有且快速增长的专用生物信息学工具手动转换为符合MCP规范的服务器，不仅劳动密集而且不可持续。在此，我们提出了BioinfoMCP，一个包含两个组件的统一平台：BioinfoMCP转换器，它利用大语言模型根据工具文档自动生成稳健的MCP服务器；以及BioinfoMCP基准测试，它系统性地验证了转换后工具在各种计算任务中的可靠性和通用性。我们展示了一个包含38个经MCP转换的生物信息学工具的平台，经过广泛验证，结果表明94.7%的工具在三个广泛使用的AI智能体平台上成功执行了复杂的工作流。通过消除AI自动化的技术障碍，BioinfoMCP使得用户无需大量编程专业知识即可通过自然语言与复杂的生物信息学分析进行交互，为通向智能、可互操作的计算生物学提供了一条可扩展的路径。