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Developers

Courses as structured data, not documents

Every Coursecast draft is structured from the start. Export it as JSON today and map it into your LMS, wiki or internal tools. A documented schema, API and webhooks are on the roadmap.

Draft and export JSON →Join the API waitlist
course.json/export
Live today
// the shape of the JSON export (values shortened)
{
  "course_title": "Incident response 101",
  "audience": "Support agents",
  "summary": "How to classify and escalate P1 incidents.",
  "learning_objectives": ["Escalate a P1 within the policy window"],
  "review_notes": ["The source doesn't define 'acknowledge'."],
  "lessons": [{
    "title": "The 15-minute notification rule",
    "objective": "Notify Tier 2 within the window",
    "estimated_minutes": 3,
    "narration_script": "When a ticket is classified P1…",
    "key_points": ["The clock starts at classification"],
    "knowledge_check": [{
      "question": "A P1 is classified at 10:02…",
      "options": ["By 10:32", "By 10:17"],
      "correct_option": 1,
      "explanation": "Policy §4.2: within 15 minutes."
    }],
    "review_notes": []
  }]
}

Field names match the app's JSON export; values are shortened examples. The format may change during early access.

Live today

JSON export

The whole course: title, audience, summary, objectives, review notes, and every lesson's script, key points and knowledge checks with the correct option and explanation.

Live today

Markdown export

Clean, structured Markdown for wikis, Notion, static sites and docs-as-code pipelines.

Roadmap

Learning IR schema

A published, versioned schema for courses with stable IDs and provenance.

Roadmap

REST API

Create drafts, read courses and releases, and trigger compiles from your systems.

Roadmap

Webhooks

Events for source changes, Training PRs, approvals and releases.

Roadmap

MCP server

Let AI assistants read approved, released course content through the Model Context Protocol, with citations.

Planned API surface

Primitives, not just "generate course"

The lifecycle as resources you can program. Design notes, not a published API.

/sourcesRoadmap

Sources

Register, version and own source documents.

/claimsRoadmap

Claims & obligations

Extracted statements with passage links.

/changesRoadmap

Change events

Diffs, materiality and blast radius.

/coursesRoadmap

Courses (Learning IR)

Typed objects with stable IDs.

/evalsRoadmap

Evals

Run checks, read results, add your own evaluator packs.

/releasesRoadmap

Releases

Manifests, approvals, compiles and rollbacks.

Rules SDK

Write your own policy rules as code for the eval lab.

Renderers & deployment adapters

Add output formats and destinations.

Source connectors

Bring a new repository into the graph.

Today

Map the export into anything

Teams already use the JSON export to seed LMS imports, generate wiki pages and feed internal knowledge tools. A tiny example in JavaScript:

No API key, no SDK: it's a file you own.

// turn an exported course into Markdown headings + quiz CSV rows
import course from "./course.json" with { type: "json" };

for (const [i, lesson] of course.lessons.entries()) {
  console.log(`## Lesson ${i + 1}: ${lesson.title}`);
  for (const q of lesson.knowledge_check ?? []) {
    console.log([q.question, ...q.options, q.options[q.correct_option]].join(","));
  }
}
Developer FAQ

Questions

Is there an API today?
No. The app is used in the browser and exports files. The API, webhooks and schema are on the roadmap; join the waitlist to shape them.
Will the JSON format change?
It may during early access. When the Learning IR schema is published, it will be versioned and documented.
What is the MCP server for?
The Model Context Protocol lets AI assistants connect to tools and data. A Coursecast MCP server would let an assistant read approved, released course content with citations. It's a connection protocol, not a monitoring or compliance system.
Which model does Coursecast use?
Anthropic's Claude, via the Claude API.

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