Last EHR — Medplum

CI License: Apache 2.0 npm: @lastehr/mcp Official MCP Registry

Add human-approved AI writeback to a FHIR app. Last EHR is the open-source reference implementation for that boundary: the agent reads the chart and proposes writes, and nothing is saved until you approve. Bring your own Medplum project and your own model key when you want a real agent, or start with the zero-key local synthetic walkthrough.

Last EHR is a layer, not an EHR. It runs on top of a headless FHIR backend (Medplum for authenticated use; HAPI FHIR, Firely Server, or Aidbox for synthetic evaluation) and talks to it over the FHIR API. It is not the system of record, stores no PHI of its own, and never bundles or forks the backend.

Status: early / alpha. APIs, structure, and scope will change. Use synthetic data only. · License: Apache-2.0

Try the live demo: no sign-up, synthetic data, and every write goes through the approval gate.

Start here

Goal	Start here
See the approval loop now	Try the live synthetic-data demo: no sign-up.
Give an MCP client bounded Medplum chart reads	npx -y @lastehr/mcp init --client claude-code
Try fixture MCP locally without FHIR credentials or a provider API key	npm run mcp:demo -- --client claude-code
Prove the synthetic web-agent workflow locally	npm run eval
Inspect the complete flow locally with no account or model key	npm run demo:local

30-second synthetic-data walkthrough

1. Open the live demo.
2. Ask: Find patients named Smith.
3. Ask: Record a heart rate of 72 bpm for Maria Garcia.
4. Inspect the proposed write, then approve it. The data is synthetic and the approval card shows exactly what will be saved.

For MCP, @lastehr/mcp is deliberately a separate read-only surface: search_patients and show_patient_info only. Configure a least-privilege Medplum token before connecting it to a real project; full setup is in the MCP guide and the Official MCP Registry listing.

Want to inspect those two MCP tools before configuring Medplum? From a checkout, npm run mcp:demo starts the included local HAPI stack, resets the four synthetic fixture charts, and prints a Claude Code/Cursor configuration. That checkout-only MCP Local Lab needs no FHIR/Medplum credentials or model-provider API key of its own and is restricted to fixture patients. Your MCP client still uses its normal account and may send those synthetic results to its model provider. It is not the published package, generic HAPI support, or a path for PHI.

For a deterministic safety-mechanics check, npm run eval creates a separate synthetic target, proves the proposal/approval and denial paths, verifies chart association, cleans up, and writes a scrubbed report. It is not a clinical, authorization, or compliance certification; see the evaluation guide.

What it does

• A chat agent (Vercel AI SDK) with FHIR tools. It reads the chart (search patients, view a patient chart) and writes to it (add a note, record an observation), streamed and rendered as structured cards.
• Writes are confirmation-gated: the agent proposes a write, you approve it, and only then is it saved. Nothing touches the chart without your click.
• Authentication, multi-tenancy, and access control are delegated to your Medplum project (Project = tenant, ProjectMembership = user, AccessPolicy = RBAC). Last EHR doesn't reimplement any of that, and writes are bounded by your AccessPolicy.

Support status

Last EHR is Medplum-supported for authenticated deployments and includes a local, no-auth HAPI FHIR mode for synthetic-data evaluation. Firely Server (FHIR_BACKEND=firely) and Aidbox (FHIR_BACKEND=aidbox) are verified synthetic-evaluation adapters: each passed both contract harnesses and the FHIR Agent Safety Eval against a disposable synthetic target. Other FHIR R4 backends need an adapter before they are supported. See the full support matrix for the web, SMART, MCP, auth, and evaluation boundaries before choosing a path.

What it isn't

• Not a charting EHR, not a system of record, and not a Medplum replacement. It's a thin agent layer: a small, growing set of tools over your FHIR backend.
• Not a guarantee. The approval gate is a human-in-the-loop boundary, not a safety proof: it stops unilateral writes, but it relies on you reading what you approve. Models can propose wrong or fabricated clinical facts, and approval fatigue is real. Last EHR provides the gate; you provide the review.

How it works

Next.js 15 (App Router) + React 19. The agent lives in app/api/chat/route.ts (streamText + FHIR tools); the FHIR calls go through a small backend interface (lib/fhir/backend.ts) with four built-in adapters: Medplum (hosted or self-hosted, token-authenticated), plus local HAPI FHIR, Firely Server, and Aidbox for synthetic evaluation. The interface is four methods plus contract notes, so an adapter for another headless EHR is a small, well-scoped contribution. See docs/adapters.md and the roadmap.

flowchart LR
    B["Browser chat"] --> A["/api/chat<br/>streamText + 4 FHIR tools"]
    A -- "reads<br/>search_patients, show_patient_info" --> M[("Your FHIR backend<br/>(Medplum, HAPI, Firely, Aidbox)")]
    A -- "writes<br/>add_note, record_observation" --> C{"Approval card"}
    C -- "Approve & save" --> M
    C -- "Cancel" --> N["Nothing saved"]
    M -. "Every call runs as the signed-in user,<br/>bounded by your AccessPolicy.<br/>The layer stores no PHI." .-> A

On the public demo, writes are also tagged with your session, so you only ever see the seed data plus your own edits.

Quickstart

Fastest: try the hosted demo at lastehr.com/demo. No account, no keys, synthetic data.

One-click deploy with your own keys:

Deploy with Vercel

You'll still need a Medplum project seeded with the synthetic patients (npm run seed, below) for the demo to have data.

Run it locally. Prerequisites: Node 22.18+ (or 24.2+), a Medplum project (Medplum-hosted free tier or your own), and one tool-capable model API key (OpenAI, Anthropic, or Amazon Bedrock).

git clone https://github.com/cbetz/last-ehr.git
cd last-ehr
npm install
cp .env.example .env.local      # then edit .env.local (see below)
npm run seed                     # load synthetic patients into your Medplum
npm run dev                      # http://localhost:3000/demo

At minimum set, in .env.local:

• a model key: OPENAI_API_KEY (default provider), or ANTHROPIC_API_KEY with AI_PROVIDER=anthropic, or AWS credentials plus AI_PROVIDER=bedrock and MODEL_ID;
• NEXT_PUBLIC_MEDPLUM_BASE_URL / MEDPLUM_BASE_URL if you're pointing at your own Medplum (leave blank to use Medplum's hosted API);
• MEDPLUM_CLIENT_ID + MEDPLUM_CLIENT_SECRET (a Medplum ClientApplication): used by npm run seed, and by the no-sign-in quickstart when you also set NEXT_PUBLIC_QUICKSTART=true. Or set NEXT_PUBLIC_MEDPLUM_GOOGLE_CLIENT_ID to sign in via Medplum's Google OAuth instead.

npm run seed loads a small synthetic patient set (scripts/fixtures/patients.ts: four patients with conditions, medications, allergies, immunizations, and vitals/labs, two named "Smith"). It wipes and recreates those patients each run, so it is safe to re-run. Then open /demo and ask: "find patients named Smith." Use synthetic data only.

Local FHIR stack, no Medplum account or model key: the repo ships a Docker Compose stack with HAPI FHIR and Postgres, plus an explicit scripted walkthrough that exercises the approval loop without calling an external model provider.

npm install
npm run demo:local                            # HAPI, seed data, and http://localhost:3000/demo

demo:local forces the local HAPI + scripted configuration without creating or overwriting .env.local. This fixed, no-network walkthrough always finds the seeded Maria Garcia record and proposes one Heart rate: 72 bpm Observation. It does not interpret your prompt, browse charts, or call a model provider; the FHIR wrapper permits only that synthetic record and observation. Press Ctrl-C to stop Next.js; use npm run demo:local:down to remove the local stack. Honest scope: the local HAPI server runs with no auth, so this mode is for local, single-tenant use only; per-browser session isolation is client-side filtering, not a security boundary. The published @lastehr/mcp package still requires Medplum credentials; the separate checkout-only npm run mcp:demo Local Lab instead exposes two synthetic, read-only charts without credentials. Neither local route is a real-data or production path. To run a real agent against HAPI, configure .env.local with a supported model key instead. The hosted public demo stays on Medplum.

To run the app container too, use npm run docker:local after filling .env.local; it combines the HAPI/Postgres compose stack with the app image. Release tags and manual publish runs push a prebuilt scripted-demo image to ghcr.io/cbetz/last-ehr; if the pull fails, no public image has been published yet. See Pull and run from GHCR.

For the longer version, see docs/quickstart.md.

Docs

• Quickstart: hosted demo, Medplum local run, and local HAPI evaluation.
• Support matrix: exactly which backends and interfaces work today.
• Architecture: the chat route, tools, backend adapters, and data boundary.
• Backend adapters: the adapter contract, harnesses, checklist, and contribution path.
• Adapter starter: an executable bearer-token FHIR REST baseline with a contract suite.
• Approval-gated writes: what the gate protects and what it does not.
• MCP server: published, read-only Medplum chart tools plus the checkout-only synthetic Local Lab.
• FHIR Agent Safety Eval: a disposable synthetic workflow report for proposal, approval, denial, association, and cleanup mechanics.
• Deployment: env vars, rate limiting, Docker, and public-demo hardening.
• Threat model: trust boundaries and known limitations.
• Roadmap: what is current, next, and deliberately out of scope.

Launch from the Medplum app (SMART on FHIR)

Last EHR can launch directly from app.medplum.com. Register it once in your Medplum project by creating a ClientApplication with:

• launchUri = https://<your-deploy>/launch
• redirectUri = https://<your-deploy>/launch/callback

then set SMART_CLIENT_ID to that ClientApplication's id in your deployment. Last EHR appears on the Apps tab of every Patient and Encounter page; launching it opens the chat already scoped to that patient, reusing your Medplum sign-in (SMART App Launch with PKCE, public client, no secret). The token is bounded by the granted SMART scopes and your AccessPolicy, and writes still stop at the approval card.

Use chart reads over MCP

@lastehr/mcp is a small, standalone MCP server for Medplum. It gives Claude Code, Cursor, and other MCP clients two bounded chart read tools, search_patients and show_patient_info, with no write tools in the 0.1.x line.

npx -y @lastehr/mcp init --client claude-code

Authenticate with a least-privilege MEDPLUM_ACCESS_TOKEN, or MEDPLUM_CLIENT_ID plus MEDPLUM_CLIENT_SECRET; set MEDPLUM_BASE_URL for a self-hosted Medplum instance. Read access can still return PHI, so review the MCP client's model-provider and data-handling boundary before connecting it to a real project.

From a checkout, npm run mcp builds and starts that same package. Full setup, client configuration, and the support boundary are in the MCP guide. The Official MCP Registry listing is the canonical discovery record for the exact, verified release.

To evaluate the MCP surface before configuring Medplum, use the separate local lab from a repository checkout:

npm install
npm run mcp:demo -- --client claude-code

It starts local HAPI, reloads the repository's synthetic fixture records, and prints a client registration command. The generated MCP process has exactly the same two read-only tool names but can only resolve those fixture patients. It is not included in @lastehr/mcp, does not make HAPI a supported package backend, and must never be pointed at real data. The Local Lab server needs no FHIR credential or provider API key, but the MCP client itself still needs its normal model account and may transmit the synthetic tool output to that model.

Configuration

Every variable is documented in .env.example. The real-agent model path is provider-agnostic with one hard rule: every external provider offered here can carry a BAA, because deployments of this project head toward real clinical data even though the demo is synthetic-only. The scripted option is a separate, explicit, zero-key local HAPI walkthrough, not a model provider or a PHI-ready mode.

AI_PROVIDER	Key	Example MODEL_ID	BAA path
scripted	None	Fixed local synthetic sequence	No external provider call. Requires explicit local HAPI flags; cannot act as a general agent.
openai (default)	OPENAI_API_KEY	gpt-4.1-mini	OpenAI signs BAAs with zero-retention options for API traffic on qualifying plans.
anthropic	ANTHROPIC_API_KEY	claude-sonnet-4-6	Anthropic signs BAAs with zero-retention options for API traffic on qualifying plans.
bedrock	AWS credential env + AWS_REGION	us.anthropic.claude-haiku-4-5-20251001-v1:0	Amazon Bedrock is available under an AWS BAA for eligible services; set an explicit model id or inference profile.

The BAA requirement applies to the external-provider rows: signing one is the operator's step, not a default, and a bare API key is not PHI-ready. Aggregators that cannot sign a BAA (OpenRouter, per their current public terms) are deliberately not offered. Analytics (PostHog) and the marketing-site waitlist (Neon) are optional and lastehr.com-specific.

Security & data

Last EHR stores no patient data of its own; everything lives in your FHIR backend. But be clear about what the approval gate is: it is a write-safety control, not a privacy control. In external-model modes, anything the agent reads from the chart is sent to your model provider as context, under your API key, with no approval step. The scripted local demo makes no model request and is restricted to its one seeded synthetic record; it is not a path for real data.

Use synthetic data unless you have real agreements in place. Pointing this at real PHI requires, at minimum:

• a BAA with your model provider that covers your API traffic (consumer plans don't qualify);
• a HIPAA-eligible FHIR backend with its own BAA;
• your own compliance review. This project is alpha and is not a HIPAA-covered service; PHI handling is the operator's responsibility.

See SECURITY.md for the full posture and how to report vulnerabilities.

Open-core

Self-hosting is free and Apache-2.0. A managed hosted tier (managed Medplum + a signed BAA, multi-tenancy, billing) may follow, built only after the open-source core has traction.

Not affiliated

A personal open-source project. Not affiliated with, endorsed by, or sponsored by Medplum, Vercel, or any employer.

License

Apache-2.0. See NOTICE for third-party attributions, CONTRIBUTING.md to contribute, and GOVERNANCE.md for how the project is run.