Server data from the Official MCP Registry
LOINC/SNOMED CT/RxNorm/ICD-10 lookup, search, translation and ValueSet expansion via FHIR.
LOINC/SNOMED CT/RxNorm/ICD-10 lookup, search, translation and ValueSet expansion via FHIR.
Valid MCP server (2 strong, 1 medium validity signals). 1 known CVE in dependencies ⚠️ Package registry links to a different repository than scanned source. Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
10 files analyzed · 2 issues found
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Set these up before or after installing:
Environment variable: TERMINOLOGY_BASE_URL
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-pcmedsinge-mcp-terminology": {
"env": {
"TERMINOLOGY_BASE_URL": "your-terminology-base-url-here"
},
"args": [
"mcp-terminology"
],
"command": "uvx"
}
}
}From the project's GitHub README.
Three coherent MCP servers for clinical AI — FHIR R4, terminologies, and clinical reasoning.
| Server | Status | Install | What it does |
|---|---|---|---|
| mcp-fhir | ✅ v1.1 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 |
Every FHIR MCP server available today (May 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:
mcp-fhir — HAPI validator sidecar, US Core + IPS profiles supported out of the box/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=sse
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"]
}
}
}
# 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
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
| Package | Version | Released |
|---|---|---|
mcp-fhir | v1.1 | June 2026 |
mcp-terminology | v1.0 | June 2026 |
mcp-clinical-reasoner | v1.0 | June 2026 |
See CONTRIBUTING.md. Apache-2.0 licensed — PRs welcome.
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