MCP 服务器

fhir-mcp-suite

Three composable MCP servers for clinical AI — FHIR R4 read/search/validate, medical terminology (LOINC/SNOMED/RxNorm/ICD-10), and drug safety reasoning (interactions, dose check, allergy). Apache-2.0, production-ready.

README

fhir-mcp-suite

Three coherent MCP servers for clinical AI — FHIR R4, terminologies, and clinical reasoning.

What's in the suite

Server	Status	Install	What it does
mcp-fhir	✅ v1.1.1 on PyPI	`uvx mcp-fhir`	FHIR R4 read/search + HAPI profile validation
mcp-terminology	✅ v1.0 on PyPI	`uvx mcp-terminology`	Unified LOINC / SNOMED / RxNorm / ICD-10 lookup + ValueSet expansion
mcp-clinical-reasoner	✅ v1.0 on PyPI	`uvx mcp-clinical-reasoner`	Drug interactions (OpenFDA), dose check, allergy conflicts

Why this suite is different

Every FHIR MCP server available today (June 2026) is a read proxy — they retrieve resources but never tell you whether the resource is valid. mcp-fhir adds HAPI profile validation as a first-class MCP tool. Composing fhir_read → validate_against_profile in one Claude session enables clinical AI pipelines that are actually safe.

Three sharp differentiators:

Profile validation built into mcp-fhir — HAPI validator sidecar, US Core + IPS profiles supported out of the box
Composable suite — three coherent servers sharing one install, one config convention, one eval harness
Production rigor — latency benchmarks, golden-query eval suite, structured JSON logs, /health + LangFuse traces

Quick start — mcp-fhir

# 1-command install (requires Python 3.12+)
uvx mcp-fhir

# Validate a Patient against US Core
# (requires HAPI validator sidecar — see docker-compose.yml)
uvx mcp-fhir --transport sse  # or set MCP_TRANSPORT=sse

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json
(Windows: %APPDATA%\Claude\claude_desktop_config.json):

{
  "mcpServers": {
    "fhir": {
      "command": "uvx",
      "args": ["mcp-fhir"],
      "env": {
        "FHIR_BASE_URL": "https://hapi.fhir.org/baseR4"
      }
    },
    "terminology": {
      "command": "uvx",
      "args": ["mcp-terminology"]
    },
    "clinical-reasoner": {
      "command": "uvx",
      "args": ["mcp-clinical-reasoner"]
    }
  }
}

Local dev stack

# Start HAPI FHIR + validator + Postgres
docker compose up hapi-fhir hapi-validator postgres

# Install workspace
uv sync

# Run unit tests
uv run pytest -m "not integration and not eval"

# Run mcp-fhir locally (stdio, points at local HAPI)
FHIR_BASE_URL=http://localhost:8081/fhir \
HAPI_VALIDATOR_URL=http://localhost:8082 \
  uv run mcp-fhir

Repo layout

fhir-mcp-suite/
├── packages/
│   ├── mcp-fhir/              # PyPI: mcp-fhir          ✅ v1.1
│   ├── mcp-terminology/       # PyPI: mcp-terminology   ✅ v1.0
│   └── mcp-clinical-reasoner/ # PyPI: mcp-clinical-reasoner ✅ v1.0
├── shared/                    # structlog, LangFuse, base Pydantic models, eval harness
├── evals/                     # golden query sets per server
├── docs/                      # MkDocs Material site
├── .github/workflows/         # ci.yml (matrix) + release.yml (per-package PyPI on tag)
├── docker-compose.yml         # all 3 + HAPI validator + Postgres
├── pyproject.toml             # uv workspace root
└── mkdocs.yml