MCP Server Healthcare

A Model Context Protocol (MCP) server for an NHS clinical coding workflow — suggesting ICD-10-CM/OPCS-4/HCC codes for a clinical note, tracking SAR/FOI information-governance requests, running DSAR mapping-repository requests through classification and clinical review, batch coding, and reading/ writing patient data via a Cerner FHIR R4 sandbox.

Any MCP client (Claude Desktop, Claude Code, Copilot Studio's MCP connector, etc.) can call these tools directly — no REST API layer required.

Originally built as part of bobbynoble/clinical-coding-bot; this repo is the standalone MCP server, with its own copy of the business logic it wraps so it has no dependency on that repo.

Tools

Area	Tools
Clinical coding	suggest_clinical_codes
SAR/FOI tracker	list_sar_foi_requests, create_sar_foi_request, update_sar_foi_request, list_overdue_sar_foi_requests, list_sar_foi_requests_due_soon, get_sar_foi_stats, get_sar_foi_cerner_bundle
DSAR mapping repository	list_dsar_types, classify_dsar_type, list_dsar_requests, create_dsar_request, get_dsar_request, review_dsar_element, deliver_dsar_request
Batch coding	list_coding_batches, get_batch_episodes, get_batch_episode, get_batch_coding_stats, get_revenue_at_risk
Cerner FHIR sandbox	cerner_status, cerner_search_patients, cerner_get_patient, cerner_get_encounters, cerner_get_discharge_note, cerner_get_documents, cerner_post_condition, cerner_post_procedure, cerner_import_encounters_to_batch, cerner_writeback_episode

cerner_post_condition, cerner_post_procedure and cerner_writeback_episode perform real writes against whatever Cerner environment is configured (a non-production sandbox by default — see app/fhir_cerner.py).

Setup

pip install -r requirements.txt
cp .env.example .env   # fill in Azure OpenAI / Search / Cerner credentials as needed

Every tool loads regardless of which credentials are set, but suggest_clinical_codes needs Azure OpenAI + Azure AI Search configured, and the cerner_* tools need CERNER_CLIENT_ID/CERNER_CLIENT_SECRET — calling one without the matching credentials fails with a clear error rather than crashing the server.

Running

Stdio (Claude Desktop, Claude Code, most local MCP clients):

python -m MCP_Server_Healthcare

Example Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "clinical-coding-bot": {
      "command": "python",
      "args": ["-m", "MCP_Server_Healthcare"],
      "cwd": "/absolute/path/to/mcp_server_healthcare"
    }
  }
}

Streamable HTTP (remote access, e.g. from Copilot Studio or a hosted MCP client):

python -m MCP_Server_Healthcare --transport http --port 8010

The HTTP transport requires CODING_API_KEY to be set in .env — every request must carry a matching X-API-Key header, or it's rejected with 401 (fails closed). It listens on 127.0.0.1 by default; set MCP_HOST=0.0.0.0 (and put it behind TLS/a reverse proxy) to expose it beyond localhost.

Repository layout

MCP_Server_Healthcare/   the MCP server itself (server.py has the tool
                         definitions; __main__.py the stdio/http entry point;
                         auth.py the HTTP transport's API-key gate)
app/                     business logic each tool wraps — coder.py (RAG
                         coding), sar_foi.py, dsar.py, batch.py,
                         fhir_cerner.py. Each stores its state in a SQLite
                         file created alongside it on first run.

Notes

• Blocking network calls (Azure OpenAI/Search, Cerner FHIR) are offloaded with asyncio.to_thread so one slow call doesn't stall other tool calls on the same server.
• SQLite files (app/sar_foi.db, app/batch.db, app/dsar.db) are created automatically on first run and are gitignored.