Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
All 94 LearnWorlds LMS API endpoints as safety-categorized MCP tools (read/write/destructive).
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
}
}
}
}Run this in your 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:1.1.2Fill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account ohneben, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.1.2) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, NexusWindows
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Windows computer use in the background: desktop apps driven without your mouse or keyboard.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
Only the beginning is shown; read the rest in the repo