About
The FHIR MCP Server provides a Model Context Protocol interface to Fast Healthcare Interoperability Resources (FHIR) APIs, enabling developers and integrators to search, retrieve, and analyze clinical information via stdio, SSE, or HTTP streams while supporting SMART‑on‑FHIR OAuth flows.
Capabilities
Overview
The FHIR MCP Server is a Model Context Protocol (MCP) implementation that translates the rich, standardized clinical data exposed by Fast Healthcare Interoperability Resources (FHIR) APIs into a format that AI assistants can consume directly. By acting as an intermediary, the server eliminates the need for developers to write custom integration code for each FHIR endpoint, allowing LLMs and other AI tools to query, retrieve, and analyze patient records with the same simple “tool‑call” syntax used for other data sources.
At its core, the server exposes a single MCP interface that understands FHIR’s RESTful patterns. It accepts standard FHIR queries—searches, reads, and bundles—and returns the results as structured JSON that the AI client can ingest. The server also implements SMART‑on‑FHIR authentication, enabling secure access to protected EHRs such as Epic or Cerner. When configured with client credentials and OAuth scopes, the server automatically handles token acquisition and renewal, so developers can focus on building higher‑level clinical workflows rather than plumbing authentication.
Key capabilities include:
- MCP‑compatible transport over stdio, Server‑Sent Events (SSE), or HTTP streams, giving clients flexibility in how they communicate.
- Full SMART‑on‑FHIR support, covering the Authorization Code Grant flow and token refresh, which is essential for compliance with healthcare privacy regulations.
- Tool integration that works out of the box with popular MCP clients like VS Code, Claude Desktop, and the MCP Inspector, allowing rapid prototyping of AI‑driven clinical assistants.
Typical use cases span a broad spectrum: an AI assistant can pull a patient’s medication list, generate discharge summaries from encounter data, or surface lab results during a virtual visit—all through declarative tool calls. In research settings, the server can feed large language models with de‑identified cohort data to support hypothesis generation or predictive modeling. Because the server abstracts both the FHIR specification and OAuth plumbing, it lowers the barrier for developers to embed clinical intelligence into conversational agents, chatbots, or decision support dashboards.
The FHIR MCP Server’s standout advantage is its zero‑code integration path. Once the server is running, any MCP‑capable client can invoke FHIR operations without writing bespoke adapters. This accelerates time‑to‑value for healthcare innovators, enabling rapid experimentation while maintaining compliance with industry standards and security best practices.
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