-
-
PatientCare
Inspiration
Healthcare systems are fragmented, and raw FHIR data is difficult for AI agents to use directly. The goal was to bridge this gap and enable interoperable, agent-ready healthcare data access.
What it does
Provides four MCP-based tools that expose structured patient data: gender, clinical conditions, medications and observations, enabling AI agents to retrieve and use standardized healthcare information.
How we built it
Built modular MCP tools on top of FHIR resources, mapping each tool to a specific clinical domain and ensuring consistent, structured data access for AI agents.
Challenges we ran into
Handling FHIR complexity, ensuring consistent data mapping across different resources, and designing tools that remain simple yet extensible for agent-based workflows.
Accomplishments that we're proud of
Successfully built interoperable tools that standardize key clinical data access and can be reused across multiple AI agents for healthcare decision support.
What we learned
Deep understanding of FHIR structure, MCP tool design, and how interoperability is critical for building scalable healthcare AI systems.
What's next for PatientCare
Expand to additional FHIR resources, integrate full agent-to-agent collaboration, and build end-to-end clinical decision support workflows.
Log in or sign up for Devpost to join the conversation.