原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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LearnWorlds

作者:ohneben版本 1.1.2i★ –i在你的电脑上运行
注册名称io.github.ohneben/learnworlds-mcp

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 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"
      }
    }
  }
}

在终端中运行这条命令

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

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "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"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

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

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 ohneben 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 18348 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 18348 个服务器的 46% 更新
  • 基础检查结果等于或优于此分类中其他 18348 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

LearnWorlds 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.1.2)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, 好縮 Short

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211前天更新
安装

好縮 Short

作者:gooonamee

Smart URL shortener: create, tag and track short links on s.gooo.name.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

只显示了开头部分;其余内容请在仓库中阅读

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