mcp-server-lims
0
The MCP Server LIMS project demonstrates an AI-driven laboratory workflow management system using simulative tools to mimic real-world lab processes. It focuses on managing sample data across multiple steps using Model Context Protocol integrations.
MCP Server LIMS
This project hosts the MCP Server code demonstrated in a LinkedIn article, showcasing an AI Agent using MCP tools to manage a lab workflow. The Laboratory Information Management System (LIMS) example capabilities include sample accessioning, preparation, analysis, and report generation. Synthetic data is used to mimic real-world lab processes, employing instruments to process and analyze samples, with results integrated into the workflow.
Introduction
- Manage data for samples in a lab workflow.
- Simulate instruments process samples for data flows.
The Example
- Workflow: samples in tubes are accessioned, processed, and analyzed.
- Simulated tags and status are randomly assigned during preparation.
Challenges for the AI Agent and Tools Integration
- AI agent manages data across workflow steps using databases.
- Specifically processes samples tagged as "passed."
- Tools accept and output arrays-of-structures in JSON.
Requirements
- Requires Python server "mcp-server-sqlite" for database functionalities.
How to Build and Run
- Ensure
uvis installed before setup and synchronization.