SEOSiri-Official/biorobotics

Overview

An open-source, stateless Model Context Protocol (MCP) framework that bridges biological datasets from NCBI and UniProt with deterministic physical coordinates for robotic automation. It enables integration of genomic and protein data into robotic control systems.

Best for

Best for
Researchers or developers integrating biological data with robotic systems

Use cases

• Automating lab workflows using genomic data
• Mapping protein sequences to physical coordinates for robotics
• Integrating NCBI/UniProt data into robotic control systems

Notes

An open-source, stateless Model Context Protocol (MCP) framework that bridges biological datasets from NCBI and UniProt with deterministic physical coordinates for robotic automation. It enables integration of genomic and protein data into robotic control systems.

0 stars on GitHub. Last updated 2026-07-27. Licensed MIT.

Use cases

• Automating lab workflows using genomic data
• Mapping protein sequences to physical coordinates for robotics
• Integrating NCBI/UniProt data into robotic control systems

Pros

• Open-source and freely available
• Stateless design simplifies scaling and deployment
• Bridges biological data with robotic automation

Cons

• Limited to specific biological datasets (NCBI/UniProt)
• Early stage with no community traction (0 stars)
• Requires MCP-compatible environment

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.