The fhir-mcp-suite server provides a comprehensive FHIR R4 interface for reading, searching, paginating, and validating clinical resources, with additional terminology and clinical reasoning capabilities.
fhir_capabilities: Retrieve a summary of the FHIR server's CapabilityStatement, including FHIR version, software info, supported resource types, and available search parameters.
fhir_read: Fetch a single FHIR R4 resource (e.g., Patient, Observation, Medication) by resource type and logical ID, returning the full resource as JSON.
fhir_search: Search any FHIR R4 resource type using standard FHIR search parameters, returning a FHIR Bundle with matching entries.
fhir_search_next: Paginate through large result sets by passing the _next_url from a previous Bundle.
validate_against_profile: Validate a FHIR R4 resource against a StructureDefinition profile using the HAPI validator, with support for US Core, IPS, and base FHIR R4 conformance — returns conformance status, error count, and detailed issues.
Terminology services: Perform unified lookups across LOINC, SNOMED, RxNorm, and ICD-10, and expand ValueSets.
Clinical reasoning: Check for drug interactions (via OpenFDA), perform dose checks, and identify potential allergy conflicts.
Three coherent MCP servers for clinical AI — FHIR R4, terminologies, and clinical reasoning.
Server | Status | Install | What it does |
mcp-fhir | ✅ v1.1.1 on PyPI |
| FHIR R4 read/search + HAPI profile validation |
mcp-terminology | ✅ v1.0 on PyPI |
| Unified LOINC / SNOMED / RxNorm / ICD-10 lookup + ValueSet expansion |
mcp-clinical-reasoner | ✅ v1.0 on PyPI |
| Drug interactions (OpenFDA), dose check, allergy conflicts |
Related MCP server: FHIR MCP Server
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
# 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=sseAdd 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"]
}
}
}# 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-fhirfhir-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.ymlPackage | Version | Released |
| v1.1 | June 2026 |
| v1.0 | June 2026 |
| v1.0 | June 2026 |
See CONTRIBUTING.md. Apache-2.0 licensed — PRs welcome.
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