Mdma

MDMA Markdown Document with Mounted Applications Interactive documents from Markdown. Built for next gen-apps

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Why MDMA?

AI conversations today are plain text — the user reads a response and manually acts on it. MDMA changes that. When an LLM knows the MDMA spec, it can respond with interactive components (forms, tables, approval gates) instead of just text. The conversation becomes actionable: the user fills out a form, approves a step, or reviews structured data — all inline, with a predictable schema that your app already knows how to render and process.

No custom UI per use case. No parsing free-form text. The AI generates structured, validated components and your frontend renders them instantly.

What is MDMA?

MDMA extends Markdown with interactive components defined in fenced mdma code blocks. A regular Markdown file becomes an interactive application:

# Patient Intake

```mdma
type: form
id: intake-form
fields:
  - name: patient-name
    type: text
    label: "Full Name"
    required: true
    sensitive: true
  - name: email
    type: email
    label: "Email"
    required: true
    sensitive: true
  - name: reason
    type: textarea
    label: "Reason for Visit"
    required: true
onSubmit: submit-intake
```

```mdma
type: button
id: submit-btn
text: "Submit Intake Form"
variant: primary
onAction: submit
```

Speed comparison

Same scenario, two models. GPT-5.5 and our own hosted MDMA-IL model.

Our model is available on Hugging Face: MobileReality/mdma-gemma4-26b-dsl-unsloth-v1

MDMA_AUTHOR prompt matrix

Each cell shows the pass rate of the model-specialized MDMA_AUTHOR prompt variant on the listed eval suite.

✅ 100% on the suite.

🟡 Scoring between 80–99% on the suite.

🔴 Scoring below 80% on the suite.