MCPmed: A Call for MCP-Enabled Bioinformatics Web Services for LLM-Driven Discovery
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912921966084096 |
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| author | Flotho, Matthias Diks, Ian Ferenc Flotho, Philipp Molano, Leidy-Alejandra G. Hirsch, Pascal Keller, Andreas |
| author_facet | Flotho, Matthias Diks, Ian Ferenc Flotho, Philipp Molano, Leidy-Alejandra G. Hirsch, Pascal Keller, Andreas |
| contents | 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 human-centric design limits machine readability for large language models (LLMs) and deep research agents. We address this gap by adapting the Model Context Protocol (MCP) to bioinformatics web server backends - a standardized, machine-actionable layer that explicitly associates webservice endpoints with scientific concepts and detailed metadata. Our implementations across widely-used databases (GEO, STRING, 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 significantly enhances automation, reproducibility, and interoperability, preparing bioinformatics web services for next-generation research agents. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_08055 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MCPmed: A Call for MCP-Enabled Bioinformatics Web Services for LLM-Driven Discovery Flotho, Matthias Diks, Ian Ferenc Flotho, Philipp Molano, Leidy-Alejandra G. Hirsch, Pascal Keller, Andreas Other Quantitative Biology 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 human-centric design limits machine readability for large language models (LLMs) and deep research agents. We address this gap by adapting the Model Context Protocol (MCP) to bioinformatics web server backends - a standardized, machine-actionable layer that explicitly associates webservice endpoints with scientific concepts and detailed metadata. Our implementations across widely-used databases (GEO, STRING, 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 significantly enhances automation, reproducibility, and interoperability, preparing bioinformatics web services for next-generation research agents. |
| title | MCPmed: A Call for MCP-Enabled Bioinformatics Web Services for LLM-Driven Discovery |
| topic | Other Quantitative Biology |
| url | https://arxiv.org/abs/2507.08055 |