Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
All 94 LearnWorlds LMS API endpoints as safety-categorized MCP tools (read/write/destructive).
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKENLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"learnworlds": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"LEARNWORLDS_BASE_URL",
"-e",
"LEARNWORLDS_API_TOKEN",
"-e",
"LEARNWORLDS_CLIENT_ID",
"-e",
"MCP_AUTH_TOKEN",
"ghcr.io/ohneben/learnworlds-mcp:1.1.2"
],
"env": {
"MCP_TRANSPORT": "your-value",
"LEARNWORLDS_BASE_URL": "your-value",
"LEARNWORLDS_API_TOKEN": "your-value",
"LEARNWORLDS_CLIENT_ID": "your-value",
"MCP_AUTH_TOKEN": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add learnworlds --env MCP_TRANSPORT=your-value --env LEARNWORLDS_BASE_URL=your-value --env LEARNWORLDS_API_TOKEN=your-value --env LEARNWORLDS_CLIENT_ID=your-value --env MCP_AUTH_TOKEN=your-value -- docker run -i --rm -e MCP_TRANSPORT -e LEARNWORLDS_BASE_URL -e LEARNWORLDS_API_TOKEN -e LEARNWORLDS_CLIENT_ID -e MCP_AUTH_TOKEN ghcr.io/ohneben/learnworlds-mcp:1.1.2Completa los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"learnworlds": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"LEARNWORLDS_BASE_URL",
"-e",
"LEARNWORLDS_API_TOKEN",
"-e",
"LEARNWORLDS_CLIENT_ID",
"-e",
"MCP_AUTH_TOKEN",
"ghcr.io/ohneben/learnworlds-mcp:1.1.2"
],
"env": {
"MCP_TRANSPORT": "your-value",
"LEARNWORLDS_BASE_URL": "your-value",
"LEARNWORLDS_API_TOKEN": "your-value",
"LEARNWORLDS_CLIENT_ID": "your-value",
"MCP_AUTH_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"learnworlds": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"MCP_TRANSPORT",
"-e",
"LEARNWORLDS_BASE_URL",
"-e",
"LEARNWORLDS_API_TOKEN",
"-e",
"LEARNWORLDS_CLIENT_ID",
"-e",
"MCP_AUTH_TOKEN",
"ghcr.io/ohneben/learnworlds-mcp:1.1.2"
],
"env": {
"MCP_TRANSPORT": "your-value",
"LEARNWORLDS_BASE_URL": "your-value",
"LEARNWORLDS_API_TOKEN": "your-value",
"LEARNWORLDS_CLIENT_ID": "your-value",
"MCP_AUTH_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub ohneben, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.1.2) llegó al registro hace 2 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Docker en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, OpenTakeoff
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Construction takeoff for AI agents: load plans, set scale, measure, count, export with provenance.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Run your LearnWorlds school in plain language from AI assistants like Claude, Cursor, and any other MCP client.
This Model Context Protocol server exposes the LearnWorlds public API — all 94 endpoints, generated straight from the OpenAPI spec into MCP tools. Every tool is safety-categorized (🟢 read-only / 🟡 write / 🔴 destructive) so your assistant knows what an action does *before* it calls it. It runs over stdio (Claude Desktop and other local launchers) or Streamable HTTP (hosted in Docker), and ships with retries, client-side rate limiting, and request timeouts so it holds up against a live school.
Some MCP servers just forward an API. This one is built to be safe to hand to an LLM and easy to run for real:
| What you get | Why it matters |
|---|---|
| All 94 endpoints, spec-driven | Full coverage of courses, users, enrollments, payments, subscriptions, coupons, certificates, seats, community and reporting — nothing hand-picked or left behind. |
| Every tool is safety-categorized 🟢 / 🟡 / 🔴 | A banner at the top of each tool description tells the model exactly what it does — read, create, update or delete — before it acts. |
| Descriptions written for agents, not humans | Every tool spells out its side effects, auth and rate-limit behavior, return shape, error codes, when *not* to reach for it, and which sibling tools are the alternatives. |
Machine-readable MCP annotations (readOnlyHint, destructiveHint) | Hosts that honor annotations (Claude included) can auto-trust reads and demand confirmation before anything destructive. |
| Automatic retries with backoff | Transient 429 / 5xx responses are retried with jittered exponential backoff, honoring the server's Retry-After header. |
| Built-in rate limiting | Self-throttles under LearnWorlds' 30 requests / 10 s cap so a burst of tool calls never trips a 429. |
| Per-request timeouts | A hung upstream call is aborted and retried instead of freezing the server. |
| **Two transports: stdio *and* Streamable HTTP** | Use it locally in Claude Desktop, or run one always-on server that any number of MCP clients reach over HTTP. |
| Docker + docker-compose, health check, auto-restart | Production-style deployment out of the box: docker compose up and it stays up. |
| Bearer-token auth on the HTTP endpoint | Required as soon as the server is bound beyond loopback: without MCP_AUTH_TOKEN it refuses to start rather than exposing the API unprotected. |
| Your secrets never reach the model | Credentials live in the server's environment and are injected on every request — the assistant only ever sees tool inputs and API responses. |
| Drop-in spec updates | LearnWorlds ships a newer YAML? Replace one file and rebuild — new endpoints become new tools automatically, no code changes. |
At the time of writing this appears to be the only dedicated LearnWorlds MCP server. You *could* instead point a generic OpenAPI→MCP wrapper at the spec — here's what that leaves on the table:
| Capability | This project | Generic OpenAPI→MCP wrapper\* |
|---|---|---|
| All 94 LearnWorlds endpoints as tools | ✅ | ✅ |
| Per-tool 🟢 / 🟡 / 🔴 safety category + banner | ✅ | ❌ |
readOnlyHint / destructiveHint MCP annotations | ✅ | ➖ |
$ref dereferencing + recursion-safe schemas | ✅ | ➖ |
Automatic retries on 429 / 5xx (honors Retry-After) | ✅ | ❌ |
| Client-side rate limiting (stays under 30 req / 10 s) | ✅ | ❌ |
| Per-request timeout with abort | ✅ | ➖ |
stdio transport | ✅ | ✅ |
| Streamable-HTTP transport | ✅ | ➖ |
| Docker + docker-compose, health check, auto-restart | ✅ | ❌ |
| Enforced bearer-token auth on the endpoint | ✅ | ❌ |
| Credentials injected server-side, never sent to the model | ✅ | ➖ |
| License | MIT | varies |
\*Generic OpenAPI→MCP wrappers turn any Swagger/OpenAPI spec into MCP tools. They can reach the same endpoints, but treat every operation identically — no safety categories, no resilience, no deployment story, and no guardrails tuned for live school data. "➖" = varies by tool / not guaranteed. Snapshot from July 2026.
Once it's connected, ask your assistant things like:
Tools are generated automatically from the API and grouped into 🟢 read-only, 🟡 write, and 🔴 destructive — so a well-behaved host can treat each group differently.
Claude / Cursor / any MCP client ──MCP──► this server ──HTTPS──► LearnWorlds API (your school)
The server parses the bundled OpenAPI spec into MCP tools (resolving $refs and guarding against recursive schemas), tags each with its safety category, and injects your bearer token and Lw-Client header on every outgoing request. Your credentials stay in the server's environment — the model never sees or handles them.
1. Add your credentials. Copy the example config and fill it in:
cp .env.example .env
2. Start the server:
docker compose up -d --build
The bundled docker-compose.yml binds to 127.0.0.1:8765 only, so the server is reachable from your machine but not the network.
3. Confirm it's running:
curl -s http://localhost:8765/health
4. Connect your MCP client. The MCP endpoint is http://localhost:8765/mcp.
mcp-remote. Add this under mcpServers in your config, then fully quit and reopen the app: {
"mcpServers": { "learnworlds": { "command": "npx", "args": [ "mcp-remote", "http://localhost:8765/mcp", "--header", "Authorization: Bearer YOUR_MCP_AUTH_TOKEN" ] } } }
(Drop the --header line if you left MCP_AUTH_TOKEN empty.)
claude mcp add --transport http learnworlds http://localhost:8765/mcp
Every push to main publishes a ready-to-run image to the GitHub Container Registry, so you can skip the local build entirely:
docker run -d --name learnworlds-mcp -p 127.0.0.1:8765:8765 --env-file .env \
ghcr.io/ohneben/learnworlds-mcp:latest
LEARNWORLDS_API_TOKEN, and your Client ID → LEARNWORLDS_CLIENT_ID.LEARNWORLDS_BASE_URL to your school's API base: https:// .learnworlds.com/admin/api. If your school uses a custom domain, use that host instead (e.g. https://academy.example.com/admin/api).Put all three in .env. The server injects them on every request, so your assistant never sees them.
Everything is set in .env (copied from .env.example):
| Variable | Required | Default | Description |
|---|---|---|---|
LEARNWORLDS_BASE_URL | ✅ | — | Your school's API base URL |
LEARNWORLDS_API_TOKEN | ✅ | — | Bearer access token |
LEARNWORLDS_CLIENT_ID | ✅ | — | Sent as the Lw-Client header |
MCP_TRANSPORT | — | stdio | stdio or http (the Docker image defaults to http) |
PORT | — | 8765 | HTTP listen port |
HOST | — | 0.0.0.0 | HTTP bind address |
MCP_HTTP_PATH | — | /mcp | HTTP MCP route |
MCP_AUTH_TOKEN | ⚠️ | _(off)_ | Require Authorization: Bearer on /mcp. Required when HOST is not a loopback address, otherwise the server refuses to start. Renamed from MCP_SHARED_TOKEN in 1.1.0 |
MCP_ALLOWED_HOSTS | — | _(automatic)_ | Comma-separated hostnames accepted in the Host header (DNS-rebinding protection). Needed behind a reverse proxy |
MCP_ALLOW_INSECURE | — | _(off)_ | Lifts the startup refusal. Only for an endpoint nobody else can reach |
MCP_SESSION_TTL | — | 1800 | Idle seconds before a session is dropped |
MCP_MAX_SESSIONS | — | 256 | Maximum concurrent sessions |
MCP_BODY_LIMIT | — | 25mb | Largest accepted request body |
LEARNWORLDS_MAX_REQUESTS | — | 25 | Client-side requests per window (0 disables throttling) |
LEARNWORLDS_RATE_WINDOW_MS | — | 10000 | Rate-limit window in ms |
LEARNWORLDS_MAX_RETRIES | — | 3 | Retries on 429 / 5xx / network errors |
LEARNWORLDS_TIMEOUT_MS | — | 30000 | Per-attempt request timeout |
LEARNWORLDS_OPENAPI_PATH | — | _(bundled)_ | Load a different OpenAPI YAML |
After changing .env, reload with docker compose up -d --force-recreate.
Each tool's description starts with one of these banners and carries the matching MCP annotations:
| Banner | Count | readOnlyHint | destructiveHint | Meaning |
|---|---|---|---|---|
| 🟢 READ-ONLY | 59 | true | false | Fetches data only. Safe. |
| 🟡 WRITE · creates data | — | false | false | POST — creates records (not idempotent; may duplicate). |
| 🟡 WRITE · updates data | — | false | false | PUT — modifies existing records in place (idempotent). |
| 🔴 DESTRUCTIVE · deletes | 8 | false | true | DELETE — removes a record. Confirm first. |
The 🟡 write tools total 27 (17 create + 10 update). Hosts that respect annotations (Claud
Solo se muestra el principio; lee el resto en el repo