Abstract Bioinformatics web servers are critical resources in modern biomedical research, facilitating interactive exploration of datasets through custom-built interfaces with rich visualization capabilities. However, this mostly human-centric design limits machine readability for large language models (LLMs) and deep research agents. We address this gap by adapting model context protocol (MCP) to bioinformatics web server backends, a standardized, machine-actionable layer that explicitly associates web service endpoints with scientific concepts and detailed metadata. Our implementations across widely used databases (GEO, STRING, and UCSC Cell Browser) demonstrate enhanced exploration capabilities through MCP-enabled LLMs. To accelerate adoption, we propose MCPmed, a community effort supplemented by lightweight breadcrumbs for services not yet fully MCP-enabled and templates for setting up new servers. This structured transition aims to significantly enhance automation, reproducibility, and interoperability, preparing bioinformatics web services for next-generation research agents.
Flotho et al. (2026) studied this question.