x=hub

your toolset

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    LearnWorlds

    mcpother
    io.github.ohneben/learnworlds-mcp · v1.1.2
    deploy just this

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

    run it

    on your own machines, one way per deploy method
    generated from the record, not tested yet
    CHANGE_ME: check the image's README for its transport and port; this assumes streamable HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command instead.
    #!/usr/bin/env bash
    # learnworlds (io.github.ohneben/learnworlds-mcp), recipe docker (generated).
    # Generated by Hub for toolset "my-agent"; started by mcp-my-agent-learnworlds.service.
    set -euo pipefail
    export HOST=127.0.0.1 PORT=8101
    exec docker run --rm --name mcp-my-agent-learnworlds -p 127.0.0.1:${PORT}:8000 --env-file /etc/mcp/my-agent.env ghcr.io/ohneben/learnworlds-mcp:1.1.2
    
    [Unit]
    Description=MCP server learnworlds (toolset my-agent), generated by Hub
    After=network-online.target docker.service
    Wants=network-online.target
    
    [Service]
    Type=simple
    User=mcp
    Group=mcp
    SupplementaryGroups=docker
    EnvironmentFile=/etc/mcp/my-agent.env
    Environment=HOME=/var/lib/mcp/learnworlds
    WorkingDirectory=/var/lib/mcp/learnworlds
    ExecStart=/opt/mcp/my-agent/bin/learnworlds.sh
    Restart=on-failure
    RestartSec=5
    NoNewPrivileges=true
    ProtectSystem=strict
    ProtectHome=true
    PrivateTmp=true
    ReadWritePaths=/var/lib/mcp/learnworlds
    
    [Install]
    WantedBy=multi-user.target
    
    generated from the record, not tested yet
    CHANGE_ME: check the image's README for its transport and port; this assumes streamable HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command instead.
    docker run --rm -p 127.0.0.1:8101:8000 -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
    
    generated from the record, not tested yet
    CHANGE_ME: check the image's README for its transport and port; this assumes streamable HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command instead.
    # Generated by Hub for toolset "my-agent" (2026-10-18T10:23:29+00:00).
    # Each package server runs behind a stdio->HTTP bridge and listens on localhost only.
    #   cp .env.example .env    # fill the ${VAR}s
    #   docker compose up -d && bash smoke.sh
    # Remote servers are not here: clients reach them directly (see clients/).
    name: mcp-my-agent
    services:
      learnworlds:
        image: ghcr.io/ohneben/learnworlds-mcp:1.1.2
        ports:
        - 127.0.0.1:8101:8000
        restart: unless-stopped
        x-note: 'CHANGE_ME: check the image''s README for its transport and port; this assumes streamable
          HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command
          instead.'
        environment:
          MCP_TRANSPORT: ${MCP_TRANSPORT}
          LEARNWORLDS_BASE_URL: ${LEARNWORLDS_BASE_URL}
          LEARNWORLDS_API_TOKEN: ${LEARNWORLDS_API_TOKEN}
          LEARNWORLDS_CLIENT_ID: ${LEARNWORLDS_CLIENT_ID}
          MCP_AUTH_TOKEN: ${MCP_AUTH_TOKEN}
    volumes:
      npm-cache: {}
      uv-cache: {}
    
    generated from the record, not tested yet
    CHANGE_ME: check the image's README for its transport and port; this assumes streamable HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command instead.
    # Generated by Hub for toolset "my-agent" (2026-10-18T10:23:29+00:00).
    #   kubectl create namespace mcp
    #   kubectl -n mcp create secret generic mcp-credentials --from-env-file=.env
    #   kubectl apply -f kubernetes.yaml
    # Services are cluster-internal: <name>.mcp.svc.cluster.local:8000/mcp. Put an ingress
    # with auth in front before exposing any of them.
    apiVersion: v1
    kind: Namespace
    metadata:
      name: mcp
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: learnworlds
      namespace: mcp
      labels: &id001
        app: learnworlds
    spec:
      replicas: 1
      selector:
        matchLabels: *id001
      template:
        metadata:
          labels: *id001
        spec:
          containers:
          - name: learnworlds
            image: ghcr.io/ohneben/learnworlds-mcp:1.1.2
            ports:
            - containerPort: 8000
              name: http
            env:
            - name: MCP_TRANSPORT
              valueFrom:
                secretKeyRef:
                  name: mcp-credentials
                  key: MCP_TRANSPORT
            - name: LEARNWORLDS_BASE_URL
              valueFrom:
                secretKeyRef:
                  name: mcp-credentials
                  key: LEARNWORLDS_BASE_URL
            - name: LEARNWORLDS_API_TOKEN
              valueFrom:
                secretKeyRef:
                  name: mcp-credentials
                  key: LEARNWORLDS_API_TOKEN
            - name: LEARNWORLDS_CLIENT_ID
              valueFrom:
                secretKeyRef:
                  name: mcp-credentials
                  key: LEARNWORLDS_CLIENT_ID
            - name: MCP_AUTH_TOKEN
              valueFrom:
                secretKeyRef:
                  name: mcp-credentials
                  key: MCP_AUTH_TOKEN
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: learnworlds
      namespace: mcp
    spec:
      selector:
        app: learnworlds
      ports:
      - port: 8000
        targetPort: http
        name: http
    
    generated from the record, not tested yet
    CHANGE_ME: check the image's README for its transport and port; this assumes streamable HTTP at :8000/mcp. If it speaks stdio only, use it from clients/mcp.json as a `docker run -i` command instead.
    # Generated by Hub for toolset "my-agent" (2026-10-18T10:23:29+00:00).
    # Credentials come from the Secret 'mcp-credentials' (kubectl create secret generic ... --from-env-file=.env).
    # Each server under `servers` is one Deployment + Service; the keys after it configure
    # upstream charts a worker verified.
    servers:
      learnworlds:
        enabled: true
        replicas: 1
        port: 8000
        path: /mcp
        container:
          name: learnworlds
          image: ghcr.io/ohneben/learnworlds-mcp:1.1.2
          ports:
          - containerPort: 8000
            name: http
          env:
          - name: MCP_TRANSPORT
            valueFrom:
              secretKeyRef:
                name: mcp-credentials
                key: MCP_TRANSPORT
          - name: LEARNWORLDS_BASE_URL
            valueFrom:
              secretKeyRef:
                name: mcp-credentials
                key: LEARNWORLDS_BASE_URL
          - name: LEARNWORLDS_API_TOKEN
            valueFrom:
              secretKeyRef:
                name: mcp-credentials
                key: LEARNWORLDS_API_TOKEN
          - name: LEARNWORLDS_CLIENT_ID
            valueFrom:
              secretKeyRef:
                name: mcp-credentials
                key: LEARNWORLDS_CLIENT_ID
          - name: MCP_AUTH_TOKEN
            valueFrom:
              secretKeyRef:
                name: mcp-credentials
                key: MCP_AUTH_TOKEN
    
    # helm install my-agent helm/my-agent -n mcp
    

    in the cloud

    one click: the provider's deploy form opens filled in, in your own account
    koyeb

    The form opens with CHANGE_ME for each value you supply: MCP_TRANSPORT, LEARNWORLDS_BASE_URL, LEARNWORLDS_API_TOKEN, LEARNWORLDS_CLIENT_ID, MCP_AUTH_TOKEN. Fill them in before you deploy.

    Clients connect to the service's https://…koyeb.app address plus /mcp.

    azure

    A Container Apps environment with one app per server, each with HTTPS ingress and one replica. The portal asks for each value you supply as a secure parameter; the deployment's outputs list the endpoints.

    connect to it

    copy what your client needs
    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
    {
      "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": "${MCP_TRANSPORT}",
            "LEARNWORLDS_BASE_URL": "${LEARNWORLDS_BASE_URL}",
            "LEARNWORLDS_API_TOKEN": "${LEARNWORLDS_API_TOKEN}",
            "LEARNWORLDS_CLIENT_ID": "${LEARNWORLDS_CLIENT_ID}",
            "MCP_AUTH_TOKEN": "${MCP_AUTH_TOKEN}"
          }
        }
      }
    }
    #!/usr/bin/env bash
    # Registers every server with Claude Code (run once; `claude mcp list` to check).
    set -euo pipefail
    set -a; [ -f .env ] && source .env; set +a
    claude mcp add learnworlds -e "MCP_TRANSPORT=${MCP_TRANSPORT}" -e "LEARNWORLDS_BASE_URL=${LEARNWORLDS_BASE_URL}" -e "LEARNWORLDS_API_TOKEN=${LEARNWORLDS_API_TOKEN}" -e "LEARNWORLDS_CLIENT_ID=${LEARNWORLDS_CLIENT_ID}" -e "MCP_AUTH_TOKEN=${MCP_AUTH_TOKEN}" -- 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
    
    {
      "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": "${MCP_TRANSPORT}",
            "LEARNWORLDS_BASE_URL": "${LEARNWORLDS_BASE_URL}",
            "LEARNWORLDS_API_TOKEN": "${LEARNWORLDS_API_TOKEN}",
            "LEARNWORLDS_CLIENT_ID": "${LEARNWORLDS_CLIENT_ID}",
            "MCP_AUTH_TOKEN": "${MCP_AUTH_TOKEN}"
          }
        }
      }
    }
    {
      "servers": {
        "learnworlds": {
          "type": "stdio",
          "command": "docker",
          "args": [
            "run",
            "-i",
            "--rm",
            "-e",
            "MCP_TRANSPORT",
            "-e",
            "LEARNWORLDS_BASE_URL",
            "-e",
            "LEARNWORLDS_API_TOKEN",
            "-e",
            "LEARNWORLDS_CLIENT_ID",
            "-e",
            "MCP_AUTH_TOKEN",
            "ghcr.io/ohneben/learnworlds-mcp:1.1.2"
          ],
          "env": {
            "MCP_TRANSPORT": "${MCP_TRANSPORT}",
            "LEARNWORLDS_BASE_URL": "${LEARNWORLDS_BASE_URL}",
            "LEARNWORLDS_API_TOKEN": "${LEARNWORLDS_API_TOKEN}",
            "LEARNWORLDS_CLIENT_ID": "${LEARNWORLDS_CLIENT_ID}",
            "MCP_AUTH_TOKEN": "${MCP_AUTH_TOKEN}"
          }
        }
      }
    }
    name: my-agent
    target: local
    servers:
    - hub: io.github.ohneben/learnworlds-mcp
    
    • not probed yet: tools unpinned, ingest lists them

    tools

    Not probed yetThe tools appear once the hub or its worker has listed this entry. Running it still works: your client lists them on first start.