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    Model Manager

    mcpkey · package
    io.github.setheerwagen/mcp-modelmanager · v1.0.3
    deploy just this

    Manage your local model machine over MCP: state, model pull/remove, service switch, LoRA training

    run it

    on your own machines, one way per deploy method
    generated from the record, not tested yet
    # once, as root:
# as_mcp DIR COMMAND...: runs COMMAND as the mcp user in DIR, its home, sandboxed as the
# units are: a package's install scripts can write to DIR only, as the server later can
as_mcp() {
  local dir="$1"; shift
  systemd-run --quiet --wait --pipe --collect --uid=mcp --gid=mcp \
    -p WorkingDirectory="$dir" -p Environment=HOME="$dir" -p ReadWritePaths="$dir" \
    -p NoNewPrivileges=true -p ProtectSystem=strict -p ProtectHome=true -p PrivateTmp=true \
    -- "$@" </dev/null
}
install -d -m 0750 -o mcp -g mcp /var/lib/mcp/modelmanager
# modelmanager: its packages, installed whole before its unit starts (no session installs)
systemctl stop mcp-my-agent-modelmanager.service 2>/dev/null || true
as_mcp /var/lib/mcp/modelmanager uv tool install mcp-modelmanager==1.0.3
as_mcp /var/lib/mcp/modelmanager uv tool install mcp-proxy

#!/usr/bin/env bash
# modelmanager (io.github.setheerwagen/mcp-modelmanager), recipe baremetal (generated).
# Generated by Hub for toolset "my-agent"; started by mcp-my-agent-modelmanager.service.
set -euo pipefail
export HOST=127.0.0.1 PORT=8101
exec uvx mcp-proxy --host 127.0.0.1 --port 8101 --pass-environment -- uvx mcp-modelmanager==1.0.3

[Unit]
Description=MCP server modelmanager (toolset my-agent), generated by Hub
After=network-online.target
Wants=network-online.target

[Service]
Type=simple
User=mcp
Group=mcp
EnvironmentFile=/etc/mcp/my-agent.env
Environment=HOME=/var/lib/mcp/modelmanager
WorkingDirectory=/var/lib/mcp/modelmanager
ExecStart=/opt/mcp/my-agent/bin/modelmanager.sh
Restart=on-failure
RestartSec=5
NoNewPrivileges=true
ProtectSystem=strict
ProtectHome=true
PrivateTmp=true
ReadWritePaths=/var/lib/mcp/modelmanager

[Install]
WantedBy=multi-user.target
    generated from the record, not tested yet
    docker run --rm -p 127.0.0.1:8101:8000 -e MM_VM_HOST -e MM_VM_USER -e MM_CONTAINER_ROOT -e MM_MAX_TIER -e MM_ENABLED_OPERATIONS -e MM_VM2_HOST ghcr.io/astral-sh/uv:python3.12-bookworm-slim sh -c 'uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-modelmanager==1.0.3'
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T17:30:13+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:
  modelmanager:
    image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
    command:
    - sh
    - -c
    - uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-modelmanager==1.0.3
    ports:
    - 127.0.0.1:8101:8000
    volumes:
    - uv-cache:/root/.cache/uv
    healthcheck:
      test:
      - CMD
      - python3
      - -c
      - import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/status')
      interval: 30s
      timeout: 5s
      retries: 5
      start_period: 2m
    restart: unless-stopped
    environment:
      MM_VM_HOST: ${MM_VM_HOST}
      MM_VM_USER: ${MM_VM_USER}
      MM_CONTAINER_ROOT: ${MM_CONTAINER_ROOT}
      MM_MAX_TIER: ${MM_MAX_TIER}
      MM_ENABLED_OPERATIONS: ${MM_ENABLED_OPERATIONS}
      MM_VM2_HOST: ${MM_VM2_HOST}
volumes:
  npm-cache: {}
  uv-cache: {}
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T17:30:13+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: modelmanager
  namespace: mcp
  labels: &id001
    app: modelmanager
spec:
  replicas: 1
  selector:
    matchLabels: *id001
  template:
    metadata:
      labels: *id001
    spec:
      containers:
      - name: modelmanager
        image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
        ports:
        - containerPort: 8000
          name: http
        env:
        - name: MM_VM_HOST
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_VM_HOST
        - name: MM_VM_USER
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_VM_USER
        - name: MM_CONTAINER_ROOT
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_CONTAINER_ROOT
        - name: MM_MAX_TIER
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_MAX_TIER
        - name: MM_ENABLED_OPERATIONS
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_ENABLED_OPERATIONS
        - name: MM_VM2_HOST
          valueFrom:
            secretKeyRef:
              name: mcp-credentials
              key: MM_VM2_HOST
        args:
        - sh
        - -c
        - uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-modelmanager==1.0.3
        readinessProbe:
          httpGet:
            path: /status
            port: http
          initialDelaySeconds: 10
---
apiVersion: v1
kind: Service
metadata:
  name: modelmanager
  namespace: mcp
spec:
  selector:
    app: modelmanager
  ports:
  - port: 8000
    targetPort: http
    name: http
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T17:30:13+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:
  modelmanager:
    enabled: true
    replicas: 1
    port: 8000
    path: /mcp
    container:
      name: modelmanager
      image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
      ports:
      - containerPort: 8000
        name: http
      env:
      - name: MM_VM_HOST
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_VM_HOST
      - name: MM_VM_USER
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_VM_USER
      - name: MM_CONTAINER_ROOT
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_CONTAINER_ROOT
      - name: MM_MAX_TIER
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_MAX_TIER
      - name: MM_ENABLED_OPERATIONS
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_ENABLED_OPERATIONS
      - name: MM_VM2_HOST
        valueFrom:
          secretKeyRef:
            name: mcp-credentials
            key: MM_VM2_HOST
      args:
      - sh
      - -c
      - uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mcp-modelmanager==1.0.3
      readinessProbe:
        httpGet:
          path: /status
          port: http
        initialDelaySeconds: 10

# 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
    deploy to koyeb

    The form opens with CHANGE_ME for each value you supply: MM_VM_HOST, MM_VM_USER, MM_CONTAINER_ROOT, MM_MAX_TIER, MM_ENABLED_OPERATIONS, MM_VM2_HOST. Fill them in before you deploy.

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

    azure
    deploy to azuretemplate

    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
    uvx mcp-modelmanager==1.0.3
# env: MM_VM_HOST, MM_VM_USER, MM_CONTAINER_ROOT, MM_MAX_TIER, MM_ENABLED_OPERATIONS, MM_VM2_HOST
    {
  "mcpServers": {
    "modelmanager": {
      "command": "uvx",
      "args": [
        "mcp-modelmanager==1.0.3"
      ],
      "env": {
        "MM_VM_HOST": "${MM_VM_HOST}",
        "MM_VM_USER": "${MM_VM_USER}",
        "MM_CONTAINER_ROOT": "${MM_CONTAINER_ROOT}",
        "MM_MAX_TIER": "${MM_MAX_TIER}",
        "MM_ENABLED_OPERATIONS": "${MM_ENABLED_OPERATIONS}",
        "MM_VM2_HOST": "${MM_VM2_HOST}"
      }
    }
  }
}
    #!/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 modelmanager -e "MM_VM_HOST=${MM_VM_HOST}" -e "MM_VM_USER=${MM_VM_USER}" -e "MM_CONTAINER_ROOT=${MM_CONTAINER_ROOT}" -e "MM_MAX_TIER=${MM_MAX_TIER}" -e "MM_ENABLED_OPERATIONS=${MM_ENABLED_OPERATIONS}" -e "MM_VM2_HOST=${MM_VM2_HOST}" -- uvx mcp-modelmanager==1.0.3

    {
  "mcpServers": {
    "modelmanager": {
      "command": "uvx",
      "args": [
        "mcp-modelmanager==1.0.3"
      ],
      "env": {
        "MM_VM_HOST": "${MM_VM_HOST}",
        "MM_VM_USER": "${MM_VM_USER}",
        "MM_CONTAINER_ROOT": "${MM_CONTAINER_ROOT}",
        "MM_MAX_TIER": "${MM_MAX_TIER}",
        "MM_ENABLED_OPERATIONS": "${MM_ENABLED_OPERATIONS}",
        "MM_VM2_HOST": "${MM_VM2_HOST}"
      }
    }
  }
}
    {
  "servers": {
    "modelmanager": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-modelmanager==1.0.3"
      ],
      "env": {
        "MM_VM_HOST": "${MM_VM_HOST}",
        "MM_VM_USER": "${MM_VM_USER}",
        "MM_CONTAINER_ROOT": "${MM_CONTAINER_ROOT}",
        "MM_MAX_TIER": "${MM_MAX_TIER}",
        "MM_ENABLED_OPERATIONS": "${MM_ENABLED_OPERATIONS}",
        "MM_VM2_HOST": "${MM_VM2_HOST}"
      }
    }
  }
}
    name: my-agent
target: local
servers:
- hub: io.github.setheerwagen/mcp-modelmanager
    • 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.