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    Mergetrain

    mcpopen · package
    io.github.yongjip/mergetrain · v3.6.0
    deploy just this

    Queue parallel-agent worktree branches, test together, serialize and recover Git pushes.

    run it

    on your own machines, one way per deploy method
    generated from the record, not tested yet
    #!/usr/bin/env bash
# mergetrain (io.github.yongjip/mergetrain), recipe baremetal (generated).
# Generated by Hub for toolset "my-agent"; started by mcp-my-agent-mergetrain.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 mergetrain==3.6.0

[Unit]
Description=MCP server mergetrain (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/mergetrain
WorkingDirectory=/var/lib/mcp/mergetrain
ExecStart=/opt/mcp/my-agent/bin/mergetrain.sh
Restart=on-failure
RestartSec=5
NoNewPrivileges=true
ProtectSystem=strict
ProtectHome=true
PrivateTmp=true
ReadWritePaths=/var/lib/mcp/mergetrain

[Install]
WantedBy=multi-user.target
    generated from the record, not tested yet
    docker run --rm -p 127.0.0.1:8101:8000 ghcr.io/astral-sh/uv:python3.12-bookworm-slim sh -c 'uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mergetrain==3.6.0'
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T12:34:05+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:
  mergetrain:
    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 mergetrain==3.6.0
    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
volumes:
  npm-cache: {}
  uv-cache: {}
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T12:34:05+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: mergetrain
  namespace: mcp
  labels: &id001
    app: mergetrain
spec:
  replicas: 1
  selector:
    matchLabels: *id001
  template:
    metadata:
      labels: *id001
    spec:
      containers:
      - name: mergetrain
        image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
        ports:
        - containerPort: 8000
          name: http
        env: []
        command:
        - sh
        - -c
        - uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mergetrain==3.6.0
        readinessProbe:
          httpGet:
            path: /status
            port: http
          initialDelaySeconds: 10
---
apiVersion: v1
kind: Service
metadata:
  name: mergetrain
  namespace: mcp
spec:
  selector:
    app: mergetrain
  ports:
  - port: 8000
    targetPort: http
    name: http
    generated from the record, not tested yet
    # Generated by Hub for toolset "my-agent" (2026-10-18T12:34:05+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:
  mergetrain:
    enabled: true
    replicas: 1
    port: 8000
    path: /mcp
    container:
      name: mergetrain
      image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
      ports:
      - containerPort: 8000
        name: http
      env: []
      command:
      - sh
      - -c
      - uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx mergetrain==3.6.0
      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

    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 deployment's outputs list the endpoints.

    connect to it

    copy what your client needs
    uvx mergetrain==3.6.0
    {
  "mcpServers": {
    "mergetrain": {
      "command": "uvx",
      "args": [
        "mergetrain==3.6.0"
      ]
    }
  }
}
    #!/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 mergetrain -- uvx mergetrain==3.6.0

    {
  "mcpServers": {
    "mergetrain": {
      "command": "uvx",
      "args": [
        "mergetrain==3.6.0"
      ]
    }
  }
}
    {
  "servers": {
    "mergetrain": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mergetrain==3.6.0"
      ]
    }
  }
}
    name: my-agent
target: local
servers:
- hub: io.github.yongjip/mergetrain
    • not probed yet: tools unpinned, ingest lists them

    tools

    Probe result: faileddocker: the container exited: ^ | File "<path>", line 306, in send_request | raise McpError(response_or_error.error) | mcp.shared.exceptions.McpError: Connection closed +------------------------------------; baremetal: MCPError: Connection closed; server stderr: …etrain.yaml --repo REPO Repository root or worktree path --db DB Override SQLite DB path core commands: {init,status,enqueue,validate,deploy,inspect} init Print or write starter config and agent docs status Show queue state and the nex…

    runs · 1

    the latest tests of this entry by the hub and its workers, newest first
    dateworkermethodstatussandboxreason
    2026-10-16 10:33 local-mac-vm docker failed gvisor docker: the container exited: ^ | File "<path>", line 306, in send_request | raise McpError(response_or_error.error) | mcp.shared.exceptions.McpError: Connectio…