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BioinfoMCP

BioinfoMCP is an open-source platform released in April 2026 by the Florensia Widjaja research team at the Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen). It automatically converts existing command-line interface (CLI)-based bioinformatics analysis tools into a Model Context Protocol (MCP) server, allowing the latest AI agents to directly control them and verify their integrity. This system enables complex genomic analysis programs and artificial intelligence.

BioinfoMCP is an open-source platform released in April 2026 by the Florensia Widjaja research team at the Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen). It automatically converts existing command-line interface (CLI)-based bioinformatics analysis tools into a Model Context Protocol (MCP) server, allowing the latest AI agents to directly control them and verifying their integrity. This system acts as an intelligent translator, connecting complex genomics analysis programs with AI models. It consists of two core layers: a Converter that automatically codes the MCP server based on tool manuals, and a Benchmark Suite that verifies the communication integrity and parameter mapping of the converted server.

Existing bioinformatics CLI tools, widely used in genomic analysis, have numerous command-line parameters and complex dependency structures. When controlled by large language models (LLMs) that communicate only in natural language, they often cause syntax errors or apply incorrect options, leading to hallucinations. Similar to how an autonomous driving system drives a car's steering and accelerator as physical control signals, BioinfoMCP builds a standardized neural network-machine interface that allows AI agents communicating in natural language to directly and accurately control legacy CLI bioinformatics analysis tools without errors. This ensures that the agent can mechanically execute bioinformatics commands without errors through a predefined, formalized schema, even without knowing complex shell syntax.

Biotechnology researchers can use this platform to analyze large-scale next-generation sequencing (NGS) data, driving the entire pipeline with intuitive natural language queries without the cumbersome bash scripting process. For example, a complex multi-step analysis process, from FastQC quality control to Bowtie2 sequence alignment and MACS3 transcription factor binding site detection, can be performed by the agent autonomously with a single request. In particular, by providing only the tool's terminal help (--help) output or PDF-format technical documentation, the AI can package code that can be directly operated within minutes, dramatically reducing the time and cost of adding new genomic analysis pipelines to a lab's unique infrastructure and automating experiments.

💻 System Requirements

🧠RAM

"CPU 환경에서 구동 가능 (OpenAI/Anthropic API 사용 시 VRAM 요구사항 없음. 로컬 LLM 구동 시 8GB+ 권장)",

💾Storage

"Conda 가상환경 구동 및 패키지 다운로드용 공간 약 1GB 이내"

Installation

4-1. Quick Start

저장소 복제 및 conda 가상 환경 생성

git clone https://github.com/florensiawidjaja/BioinfoMCP.git cd BioinfoMCP conda create -n bioinfomcp-env python=3.10 -y conda activate bioinfomcp-env

필수 패키지 설치

pip install fastmcp openai

4-2. 상세 설치

1. API 키 설정 (.env 파일 생성)

echo "OPENAI_API_KEY=your_openai_api_key" > .env echo "OPENAI_MODEL=gpt-4o-mini" >> .env

2. CLI 도구의 manual 또는 --help 텍스트를 기반으로 MCP 서버 자동 변환 실행

python -m main --name fastqc --manual "--help" --run_help_command True --output_location ./output/

3. (옵션) Conda 가상 환경에 분석하고자 하는 실제 생물정보학 도구(예: FastQC) 설치

conda install -c bioconda fastqc -y

FAQ

What is BioinfoMCP?

BioinfoMCP is an open-source platform released in April 2026 by the Florensia Widjaja research team at the Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen). It automatically converts existing command-line interface (CLI)-based bioinformatics analysis tools into a Model Context Protocol (MCP) server, allowing the latest AI agents to directly control them and verifying their integrity. This system acts as an intelligent translator, connecting complex genomics analysis programs with AI models. It consists of two core layers: a Converter that automatically codes the MCP server based on tool manuals, and a Benchmark Suite that verifies the communication integrity and parameter mapping of the converted server. Existing bioinformatics CLI tools, widely used in genomic analysis, have numerous command-line parameters and complex dependency structures. When controlled by large language models (LLMs) that communicate only in natural language, they often cause syntax errors or apply incorrect options, leading to hallucinations. Similar to how an autonomous driving system drives a car's steering and accelerator as physical control signals, BioinfoMCP builds a standardized neural network-machine interface that allows AI agents communicating in natural language to directly and accurately control legacy CLI bioinformatics analysis tools without errors. This ensures that the agent can mechanically execute bioinformatics commands without errors through a predefined, formalized schema, even without knowing complex shell syntax. Biotechnology researchers can use this platform to analyze large-scale next-generation sequencing (NGS) data, driving the entire pipeline with intuitive natural language queries without the cumbersome bash scripting process. For example, a complex multi-step analysis process, from FastQC quality control to Bowtie2 sequence alignment and MACS3 transcription factor binding site detection, can be performed by the agent autonomously with a single request. In particular, by providing only the tool's terminal help (--help) output or PDF-format technical documentation, the AI can package code that can be directly operated within minutes, dramatically reducing the time and cost of adding new genomic analysis pipelines to a lab's unique infrastructure and automating experiments.

When should I use BioinfoMCP?

BioinfoMCP is an open-source platform released in April 2026 by the Florensia Widjaja research team at the Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen). It automatically converts existing command-line interface (CLI)-based bioinformatics analysis tools into a Model Context Protocol (MCP) server, allowing the latest AI agents to directly control them and verify their integrity. This system enables complex genomic analysis programs and artificial intelligence.

📄 Official Docs🐙 GitHub

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