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omcp

MCP.Pizza Chef: fastomop

OMCP is a Model Context Protocol server designed for the Observational Medical Outcomes Partnership (OMOP) Common Data Model. It provides a standardized interface for AI models to query, analyze, and interact with healthcare data formatted in OMOP, facilitating advanced medical data research and insights through seamless integration with LLMs.

Use This MCP server To

Query OMOP healthcare datasets using natural language Analyze patient outcomes with AI-driven data exploration Integrate OMOP data into AI-powered clinical decision tools Standardize access to observational medical data for models Enable real-time AI analysis of healthcare records Support research by exposing OMOP data via MCP Facilitate multi-step reasoning on medical datasets

README

omcp FAQ

How does OMCP connect AI models to OMOP data?
OMCP exposes OMOP Common Data Model healthcare data through the MCP server interface, allowing AI models to query and analyze it seamlessly.
What types of healthcare data can OMCP handle?
OMCP supports the full range of observational medical data standardized in the OMOP Common Data Model, including patient records, treatments, and outcomes.
Is OMCP compatible with multiple LLM providers?
Yes, OMCP works with various LLMs such as OpenAI, Anthropic Claude, and Google Gemini by providing a standardized data interface.
Where can I find documentation for OMCP?
Full documentation is available at https://fastomop.github.io/omcp/ for setup, usage, and API details.
Can OMCP support real-time querying of healthcare data?
Yes, OMCP is designed to enable real-time AI queries and analysis on OMOP datasets.
How secure is the data access through OMCP?
OMCP follows MCP principles for secure, scoped, and observable model interactions to protect sensitive healthcare data.
What programming languages or platforms does OMCP support?
OMCP is implemented as an MCP server and can be integrated with any platform supporting MCP clients and LLMs.
Can OMCP be extended to other healthcare data models?
Currently focused on OMOP, but its MCP server architecture allows potential extension to other standardized healthcare data models.