atlas-mcp

# hc-ai-mcp An MCP server that brings AI-powered search and conversation to your FHIR clinical documents.     ## What It Does `hc-ai-mcp` is a developer-focused MCP server for working with FHIR data. It lets you embed FHIR resources, search them with semantic retrieval, and talk to an AI agent that can answer questions with citations from your clinical documents. - AI agent that understands and queries FHIR documents - Semantic search with cross-encoder reranking for accuracy - Multi-turn conversations with session memory - Local-first LLM support (Ollama), plus cloud options (OpenAI, Anthropic, Bedrock) ## Key Features - Native FHIR resource handling and metadata extraction - Vector embeddings plus access to full documents - Built-in validation and HIPAA-aware prompts - YAML + environment configuration for easy setup ## Quick Start (5 Minutes) ### 1) Clone and Install ```bash git clone https://github.com/rsanandres/hc-ai-mcp.git cd hc-ai-mcp python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt ``` ### 2) Set Up PostgreSQL + pgvector ```bash createdb hc_ai psql -U postgres -d hc_ai -f scripts/setup_db.sql ``` ### 3) Configure Environment ```bash cp env.example .env # Edit .env and set DB_PASSWORD at minimum ``` ### 4) Start Ollama (Local-First) ```bash ollama pull mxbai-embed-large:latest ollama pull llama3 ollama serve ``` ### 5) Run the Server ```bash # stdio transport (Claude Desktop, Cursor) python server.py # HTTP transport python server.py --transport streamable-http --port 8000 ``` ## Architecture ```mermaid flowchart TB subgraph clients [MCPClients] Claude[Claude Desktop] Cursor[Cursor IDE] Custom[Custom…