让生物信息工具一键对接AI agent，实现自然语言操作
BioinfoMCP: A Unified Platform Enabling MCP Interfaces in Agentic Bioinformatics
- 用大模型自动把工具文档转为标准MCP接口服务器
- 38个工具经验证94.7%可在三大AI平台成功运行复杂流程
- 适合无编程基础的研究者快速构建智能生物分析流程
生物信息学工具对复杂计算生物学任务至关重要，但与新兴AI代理框架的集成受制于接口不兼容、输入输出格式异构及参数规范不一。模型上下文协议（MCP）提供了标准化的工具-AI通信框架，但手动将数百个现有且持续增长的专业生物信息工具转换为MCP兼容服务器既费力又不可持续。本文提出BioinfoMCP统一平台，包含两个组件：基于大语言模型自动从工具文档生成稳健MCP服务器的BioinfoMCP Converter，以及系统评估转换后工具在多样化计算任务中可靠性与通用性的BioinfoMCP Benchmark。我们构建了38个经MCP转换的生物信息工具平台，经广泛验证显示，在三个主流AI代理平台上，94.7%的成功执行了复杂工作流。该平台消除了AI自动化的技术壁垒，使用户无需大量编程即可通过自然语言交互完成复杂生物信息分析，为智能化、互操作性计算生物学提供了可扩展路径。
原文摘要 · Abstract (English)
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.
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