# Anpheros for AI developers

> Building healthcare software with Claude Code, Cursor, GitHub Copilot, ChatGPT, Gemini, Grok or Ollama on top of Anpheros as the medical-data layer: machine-readable docs, SDKs and the sandbox.

Source: https://developers.anpheros.com/guides/ai-developers

**Whether you build with Claude Code, Cursor, GitHub Copilot, ChatGPT, Gemini, Grok, Ollama or another AI development environment, Anpheros can serve as the medical-data infrastructure layer of your healthcare application.** AI tools are fast at generating application code, but a medical application also needs a data model, consent, provenance and an audit trail that a generated prototype rarely gets right. Building on Anpheros means the generated code calls a tested medical-data API instead of inventing its own medical database.

There is no official plugin or integration between Anpheros and any of these tools or models. What Anpheros offers are machine-readable resources that any assistant or agent can read, typed SDKs, and a sandbox where generated code can run safely.

## Two ways AI shows up in your project

| | AI helps you write the software | AI is part of the software |
|---|---|---|
| Examples | Claude Code, Cursor, GitHub Copilot, ChatGPT writing your code | your app calls a model (hosted, or local with Ollama) to answer health questions |
| What Anpheros gives you | an API and docs your coding assistant can follow | the patient context for the model, with consent and audit |
| Read next | this page | [AI healthcare applications](https://developers.anpheros.com/guides/ai-healthcare) |

## Give your coding assistant the right context

| Resource | URL | Why it helps |
|---|---|---|
| OpenAPI specification | `https://developers.anpheros.com/openapi.json` | every endpoint with request and response schemas |
| Developer summary | `https://developers.anpheros.com/llms.txt` | what the platform is and where each topic is documented |
| All guides in one file | `https://developers.anpheros.com/llms-full.txt` | the guides as Markdown, for a single context load |
| Each guide as Markdown | `https://developers.anpheros.com/guides/{guide}.md` | e.g. `/guides/getting-started.md` |
| FHIR CapabilityStatement | `https://platform.anpheros.com/fhir/R4/metadata` | the 26 FHIR resource types and their search parameters |
| Typed SDKs | `@anpheros/sdk` (npm), `anpheros_sdk` (pub.dev) | idempotency keys, retries, token refresh and the consent flow already implemented |

A practical first instruction: *"Use Anpheros Platform as the medical-data backend. Read https://developers.anpheros.com/llms.txt and the OpenAPI spec before writing code. Use the TypeScript SDK. Use the sandbox key from the environment variable `ANPHEROS_KEY`."*

## When your assistant asks where to store patient data

Coding assistants tend to propose new tables for patients, observations and medications. For a healthcare application built on Anpheros, point them to the medical data layer instead: patient records go to the Anpheros HL7 FHIR R4 store through the SDK, and your own database keeps users, sessions and product data. A sentence you can give your assistant: *"Store all patient medical data in Anpheros through `@anpheros/sdk` (patients, observations, conditions, medications, documents); do not create tables for medical data; keep only the mapping from our user id to the Anpheros patient id."*

## Let generated code run in the sandbox

The sandbox is a separate database, and each sandbox project has its own copy of 30 synthetic patients. A sandbox key (`sk_test_`) physically cannot reach real patients, so an assistant can create patients, write observations and run tests without touching real medical data — and a reset brings the synthetic patients back as they were.

- Put the sandbox key in an environment variable; never paste keys into prompts or commit them.
- Never give a coding assistant a production key (`sk_live_`).
- Requests with the same `Idempotency-Key` are safe to retry — useful when an assistant re-runs a script.

## Keep the medical rules in the platform, not in generated code

Ask your assistant to rely on Anpheros for the parts that are easy to get wrong:

- **Consent:** OAuth grants and scopes instead of home-made permission tables.
- **Provenance:** `author_type` on every write (`patient`, `practitioner`, `device`, `import`, `ai`) instead of an invented "source" column.
- **Standards:** LOINC for measurements, ICD-10 for conditions, ATC for medications; `GET /v1/terminology/loinc?q=…` and `/v1/terminology/atc?q=…` search the bundled code subsets.
- **Errors:** the documented error types and the `Anpheros-Request-Id` header ([Errors](https://developers.anpheros.com/guides/errors)).

## A first script an assistant can generate

```ts
import { Anpheros, apiKey } from '@anpheros/sdk';

const anpheros = new Anpheros({ auth: apiKey(process.env.ANPHEROS_KEY!) });   // sk_test_ key

const { data: patients } = await anpheros.patients.list();                    // synthetic sandbox patients
const labs = await anpheros.observations.list(patients[0].id, { category: 'laboratory', limit: 10 });
const ctx = await anpheros.context.build({ patient: patients[0].id, task: 'weekly check-in', budget_tokens: 1500, format: 'text' });
console.log(labs.data, ctx.text);
```

## When your application also uses a model

The same project can call a model at runtime: request a context from Anpheros and pass it to a hosted model or to a local one (for example through Ollama). How to do that safely — consent, budgets, provenance in the prompt, what to show the user — is covered in [LLM applications and healthcare data](https://developers.anpheros.com/guides/llm-healthcare-data) and [AI medical assistant](https://developers.anpheros.com/guides/ai-medical-assistant).

## Related

- [FHIR MCP server for AI agents](https://developers.anpheros.com/guides/mcp)
- [Build a healthcare app](https://developers.anpheros.com/guides/build-a-healthcare-app)
- [Build with Anpheros](https://developers.anpheros.com/guides/build-with-anpheros)
- [AI agents and medical data](https://developers.anpheros.com/guides/ai-agents-medical-data)
- [SDKs](https://developers.anpheros.com/guides/sdks)