MCP Healthcare Server

A Model Context Protocol (MCP) server for clinical workflows, built per the design in deep-research-report.md. The server exposes a governed set of tools (patient lookup, appointment booking, prescription, drug-interaction check, symptom triage, lab results, insurance eligibility, telehealth) and enforces role-based access control and audit logging on every call.

This implementation is a development scaffold: data is held in memory (seeded from src/data/*.json) and there is no real EHR/FHIR integration. It is a safe environment to exercise the MCP surface and the security enforcement layer.

Quick start

npm install
npm run dev     # tsc-watch-style restart on src changes
# or
npm run build && npm start

The server speaks MCP over stdio and is ready to attach to any MCP-aware client (Claude Desktop, MCP Inspector, custom agents).

Related MCP server: openemr-mcp

Tool surface

Every tool call must include a userId from src/data/users.json. The server resolves the user, checks role permissions, then runs the handler. Denials and runtime errors are recorded in the audit log.

Security model

• Audit log — one JSON line per call to logs/audit-<YYYY-MM-DD>.log. Captures timestamp, userId, tool, SHA-256 of the input (16 hex chars — avoids writing PHI in plaintext), outcome, and duration.

• RBAC — defined in src/auth/rbac.ts. Read tools accept any clinical role. Write tools require clinician or admin. Pharmacy tools also accept pharmacist. Unknown user → denial.

• Input validation — Zod schemas on every tool; the MCP SDK rejects malformed inputs before the handler runs.

File layout

src/
  index.ts                 # bootstrap (stdio transport)
  server.ts                # createServer(): McpServer + audit + exit hooks
  config.ts                # env loading (LOG_DIR, DATA_DIR)
  types.ts                 # domain types
  audit/logger.ts          # append-only audit log
  auth/rbac.ts             # user lookup + role checks
  store/memoryStore.ts     # in-memory store + loadSeed()
  tools/
    registry.ts            # central tool context + module list
    patient.ts             # search_patient, get_patient_history
    appointment.ts         # find_available_slots, book, reschedule
    prescription.ts        # create_prescription, check_drug_interaction, get_active_medications
    symptoms.ts            # analyze_symptoms, suggest_specialist
    lab.ts                 # get_recent_lab_results, analyze_lab_results
    eligibility.ts         # check_eligibility, create_prior_authorization_request
    telehealth.ts          # create_telehealth_session, send_telehealth_link
  data/                    # seed JSON (patients, providers, drugs, labs, etc.)
logs/                      # audit log output (gitignored)

Seed users (for testing)

Out of scope (TODO for production)

• Real FHIR / HL7 / PACS / DICOM adapters

• OAuth2 / SMART-on-FHIR launch

• Persistent database (in-memory only)

• LLM-backed symptom analysis (rule-based placeholder)

• HIPAA-grade audit retention, encryption at rest, key rotation

• Rate limiting, network segmentation

References

See deep-research-report.md for the full design rationale, architecture options, compliance checklist, and roadmap that informed this implementation.