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LearnWorlds

by ohnebenversion 1.1.2i★ –iRuns on your computer
Registry nameio.github.ohneben/learnworlds-mcp

Install

Overview

Description from the maker (original English)

All 94 LearnWorlds LMS API endpoints as safety-categorized MCP tools (read/write/destructive).

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other
  • You need to fill in: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

Values 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:1.1.2

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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.

Open in VS Code

Or copy the settings yourself

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.

Values you fill in

  • MCP_TRANSPORT required env
    Server transport. Set to 'stdio' for local MCP clients; the image otherwise starts the Streamable HTTP transport.
  • LEARNWORLDS_BASE_URL required env
    Base URL of your LearnWorlds school's API, e.g. https:// .learnworlds.com/admin/api
  • LEARNWORLDS_API_TOKEN secret required env
    Bearer access token (LearnWorlds admin -> Settings -> Integrations -> Developers).
  • LEARNWORLDS_CLIENT_ID secret required env
    Your school's Client ID, sent as the Lw-Client header.
  • MCP_AUTH_TOKEN secret env
    Only for MCP_TRANSPORT=http: bearer token required on /mcp. Without it a non-loopback bind refuses to start.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account ohneben, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18336 servers in this category
  • Published to the registry more recently than 46% of the other 18336 servers in this category
  • Basic checks equal to or better than 100% of the other 18336 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is LearnWorlds safe?

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.

What keys or codes does it need?

You need to fill in: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.1.2) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, NexusWindows

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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NexusWindows

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Runs on your computerUpdated today
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README from the maker

Open the README

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.

ohneben's LearnWorlds MCP


License & checks
MCP registries

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.

Why you'll want this

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 getWhy it matters
All 94 endpoints, spec-drivenFull 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 humansEvery 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 backoffTransient 429 / 5xx responses are retried with jittered exponential backoff, honoring the server's Retry-After header.
Built-in rate limitingSelf-throttles under LearnWorlds' 30 requests / 10 s cap so a burst of tool calls never trips a 429.
Per-request timeoutsA 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-restartProduction-style deployment out of the box: docker compose up and it stays up.
Bearer-token auth on the HTTP endpointRequired 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 modelCredentials 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 updatesLearnWorlds ships a newer YAML? Replace one file and rebuild — new endpoints become new tools automatically, no code changes.
How it compares

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:

CapabilityThis projectGeneric 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✅➖
LicenseMITvaries

\*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.

What you can do

Once it's connected, ask your assistant things like:

  • "List the 10 most recent users who signed up this month."
  • "Create a user for jane@example.com and enroll her in the 'Pro' bundle."
  • "Show me this month's payments and total revenue."
  • "Which users haven't completed the 'Onboarding' course yet?"
  • "Create a 20%-off coupon for the annual subscription plan."
  • "Pull completion analytics for our top 5 courses."

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.

How it works

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.

Requirements

  • A LearnWorlds school with API access — an access token and a Client ID (admin → Settings → Integrations → Developers), plus your school's API base URL. See Get your API credentials.
  • Docker (Docker Desktop on macOS/Windows) for the quick start below — or Node.js ≥ 18 to run from source.

Quick start (Docker)

1. Add your credentials. Copy the example config and fill it in:

cp .env.example .env

edit .env → set LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID

→ set MCP_AUTH_TOKEN (required once the port is published beyond

127.0.0.1): openssl rand -hex 32

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

→ {"status":"ok","server":"learnworlds-mcp","tools":94}

4. Connect your MCP client. The MCP endpoint is http://localhost:8765/mcp.

  • Claude Desktop — add a custom connector (Settings → Connectors) pointing at the URL, or bridge it locally with 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 Code — one command:
  claude mcp add --transport http learnworlds http://localhost:8765/mcp
  • Claude Cowork — shares Claude Code's MCP config, so the command above makes the tools available there too.
Prefer a prebuilt image?

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

Get your API credentials

  1. Log in to your LearnWorlds school admin.
  2. Go to Settings → Integrations → Developers (the API screen).
  3. Copy your Access Token → LEARNWORLDS_API_TOKEN, and your Client ID → LEARNWORLDS_CLIENT_ID.
  4. Set 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.

Configuration

Everything is set in .env (copied from .env.example):

VariableRequiredDefaultDescription
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—stdiostdio or http (the Docker image defaults to http)
PORT—8765HTTP listen port
HOST—0.0.0.0HTTP bind address
MCP_HTTP_PATH—/mcpHTTP 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—1800Idle seconds before a session is dropped
MCP_MAX_SESSIONS—256Maximum concurrent sessions
MCP_BODY_LIMIT—25mbLargest accepted request body
LEARNWORLDS_MAX_REQUESTS—25Client-side requests per window (0 disables throttling)
LEARNWORLDS_RATE_WINDOW_MS—10000Rate-limit window in ms
LEARNWORLDS_MAX_RETRIES—3Retries on 429 / 5xx / network errors
LEARNWORLDS_TIMEOUT_MS—30000Per-attempt request timeout
LEARNWORLDS_OPENAPI_PATH—_(bundled)_Load a different OpenAPI YAML

After changing .env, reload with docker compose up -d --force-recreate.

Tool safety categories

Each tool's description starts with one of these banners and carries the matching MCP annotations:

BannerCountreadOnlyHintdestructiveHintMeaning
🟢 READ-ONLY59truefalseFetches data only. Safe.
🟡 WRITE · creates data—falsefalsePOST — creates records (not idempotent; may duplicate).
🟡 WRITE · updates data—falsefalsePUT — modifies existing records in place (idempotent).
🔴 DESTRUCTIVE · deletes8falsetrueDELETE — 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

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