FHIR Healthcare

This MCP server provides AI assistants with comprehensive FHIR healthcare data access and document search capabilities, built using Python with FastAPI and featuring specialized tools for each FHIR resource type (Patient, Observation, Condition, etc.) plus RAG-powered document analysis through Pinecone vector search. The implementation offers OAuth2-authenticated FHIR server integration with Medplum, semantic document processing using HuggingFace embeddings for medical literature, LOINC code lookup for standardized medical terminology, and specialized tools for healthcare workflows including patient data management, clinical observations, and medical document ingestion with intelligent search. Built with Docker containerization, cryptographic configuration management, and robust error handling across FHIR operations and vector database interactions, it serves healthcare AI applications requiring natural language access to electronic health records, clinical research workflows needing conversational FHIR data exploration, and medical documentation systems where AI-driven patient data analysis enhances clinical decision-making without direct FHIR API knowledge.