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his-tools

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his-mcp-agents

An MCP server for hospital information system (HIS) data, plus a supervisor/worker agent graph that writes a grounded pre-visit brief for a clinician.

Portfolio demo (Sept 2026). Mock FHIR-shaped data, runs fully offline, 8 tests. It shows the design decisions I would make when putting LLM agents next to an HIS — not a production system.

               MCP (stdio)                         read-only, de-identified
 LLM / agent  ───────────────►  his-tools server  ───────────────────────►  FHIR store
                                 │  every call → audit.jsonl
                                 │  writes = draft only; clinician confirms out-of-band

What it demonstrates

Concern

How it is handled

PHI never reaches the model

Tools return a pseudonymous pid (HMAC-SHA256), an age band and gender — no names, national IDs or birth dates (his_mcp/deid.py)

Auditability

Every tool call is appended to audit.jsonl with actor, tool, hashed args, model and prompt version (his_mcp/audit.py)

Human-in-the-loop writes

The agent can only call draft_medication_request; it returns a single-use token. confirm_medication_request is not exposed over MCP — only the clinician UI can call it (test_confirm_is_not_an_mcp_tool)

Grounding

The brief is built only from tool results and guideline chunks, each line carries [tool:…] or [file.md:Lx]

Multi-agent routing

LangGraph: gather → supervisor → guidelines? → interactions? → writer. The supervisor skips workers that have nothing to do (single-med patient ⇒ no interaction check)

Cost / latency visibility

Every node appends ms, token estimate, model and prompt_version to trace — the basis for TTFT and per-call cost tracking

Model-agnostic

LLM_BACKEND=template (default, deterministic), ollama (local — keeps data on-prem), or anthropic

Related MCP server: FhirMCP

Run

pip install -r requirements.txt
pytest -q                          # 8 tests
python -m agents.graph             # prints the brief + per-node trace
python -m his_mcp.server           # MCP server over stdio (e.g. register in Claude Desktop)
LLM_BACKEND=ollama OLLAMA_MODEL=qwen2.5:7b python -m agents.graph

Tools exposed

list_patients · get_encounters · get_conditions · get_observations(abnormal_only) · get_medications · check_interactions(extra_drugs) · draft_medication_request

Limits (on purpose)

  • Mock data; the interaction table has three illustrative pairs and is not clinical knowledge.

  • BM25 over markdown stands in for a vector store; the retrieval interface is the same.

  • Guideline texts are short illustrative summaries I wrote, not clinical guidance.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

Related MCP Connectors

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