GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Queue parallel-agent worktree branches, test together, serialize and recover Git pushes.
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。
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。
选择你使用的 AI 应用,然后复制设置。
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": {
"mergetrain": {
"command": "uvx",
"args": [
"mergetrain",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add mergetrain -- uvx mergetrain mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"mergetrain": {
"command": "uvx",
"args": [
"mergetrain",
"mcp"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"mergetrain": {
"type": "stdio",
"command": "uvx",
"args": [
"mergetrain",
"mcp"
]
}
}
}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。
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。
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8日
注册名称已通过 GitHub 账户 yongjip 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
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)。
GitHub 仓库最后更新于–,最新版本(3.7.1)于12天前进入注册中心。
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 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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。
Safely integrate committed branches from parallel coding agents.
mergetrain is a local merge queue for parallel LLM agents. These coding agents use large language models and work in Git worktrees. mergetrain runs on your machine. A train is a group of queued task branches. A gate is a configured test or check. Each agent commits and enqueues its branch. One runner merges branches in enqueue order and runs gates on the combined result. It updates your Git refs atomically only after explicit approval.
mergetrain is designed for one operator managing local repositories.
There is no mergetrain account, hosted control plane, OAuth app, or product telemetry. Queue and runner state stay on your machine. Only your configured Git remote and trusted gate or verification commands may contact external services.
Default batch mode: passing work lands first. Work that needs a fix returns to its agent. Passing work can land while the repair continues.
Keep building during checks. Agents start their next task while mergetrain checks earlier work. This 14-second loop keeps the same four agents in view.
Agents can keep building in both modes. In ordered mode, an unresolved earlier submission holds later landings. Compare the two modes.
Pause or replay the demo · View the still image · Reproduce the continuous workflow
How this demo was made
This illustration follows recorded CLI results. The four lanes represent agent roles; letters identify work, not queue job IDs. The capture scripts agent-authored changes and operator approvals in a disposable local repository and bare remote. It does not launch an AI service.
Two fixture gate waits make the overlaps reproducible: E and F are committed during A and B validation, then G and H drafts start during E and F validation. All three deployments retain approval and the default recheck. A fresh clone of the final remote passes six tests.
G and H then refresh onto that result without losing their edits. I and J start there too. These four drafts remain unsubmitted. Your agents or operator create, fix, refresh and resubmit work; mergetrain checks and integrates it. The 14-second animation repeats this recorded window with condensed timing.
Worktrees let several agents edit one repository without sharing a checkout. They do not decide landing order, test the combined result, prevent push races, or tell you what happened if a laptop dies mid-push.
Without a shared integration workflow, the operator chooses branch order and resolves cross-branch failures. The operator also reruns tests and controls pushes. Repeating these actions can slow parallel work.
mergetrain records this workflow in a durable local queue:
agent branches → local queue → isolated integration worktree → combined gates
→ explicit approval → one atomic push → post-push verification
Use mergetrain when:
It is harness-agnostic: Codex, Claude Code, agy, scripts, and humans all use the same CLI and JSON contract.
Running several Claude Code or Codex sessions on one laptop? The one-laptop guide covers worktrees, unattended landing, heavy gates, sleep and quiet periods, a push guard, and outcome reports, each tested in disposable repositories.
You probably do not need mergetrain when:
For PR-first teams, use GitHub Merge Queue or GitLab Merge Trains. mergetrain is for local-agent, worktree-first integration, with or before a PR.
Start with `batch`, the default. It suits independent work from parallel agents. The runner combines the queued work available when it starts; it does not wait for every agent to finish. Compatible work can land while an agent repairs a failed submission.
Use ordered when each change needs its own landing and the original submission order must survive a failure and retry.
| Comparison | batch (default) | ordered (optional) |
|---|---|---|
| Agent work example | A fixes login, B adds search filters, C updates the admin screen | A, B, and C make compiler optimizations; measure each change against the previous landed result |
| Landing unit | Available submissions together | One submission at a time |
| If B fails | After isolating B and passing checks on A+C, A+C can land | A can land; C waits until B is repaired and lands, or is explicitly canceled |
B after retry | Joins the back of the queue | Keeps B's original position, before C |
Both modes let agents start their next task after handoff. Both keep deploy approval and the default pre-push recheck. Ordered processing can run checks more often because each submission lands separately. Queue order starts at submission, not when an agent starts work, and does not express code dependencies. Order ends at a successful Git landing. Post-push verification warnings remain visible while later work proceeds; an uncertain push still requires reconciliation.
Availability: ordered is available in 3.6.0 and newer. Keep the default batch for ordinary parallel agent work. See the agent work examples, configuration, and upgrade procedure.
Lease tokens fence concurrent and stale mergetrain runners. They do not intercept an arbitrary git push from a task agent that has shell access and an integration-branch credential. To make “one runner owns the push” an enforced property rather than a protocol assumption, use this topology:
task agents: commit + exact-SHA enqueue; no integration push credential
runner: separate deploy identity remote: protected integration branch; runner or reviewed PR path only
Without credential separation and remote protection, mergetrain still provides safe train assembly and recovery semantics, but it cannot prevent a participant from bypassing the queue. See the security boundary.
uvx mergetrain demo
The demo creates a disposable repository and local bare remote, then runs four real branches through merges in enqueue order, a combined-only gate failure, conflict attribution, and deployment of the compatible train. Use --keep to inspect the result afterward. Add --brief --pause to read each step before continuing. The extended workflow recording adds repair, work committed during validation, the next batch, and three verified local deployments.
Full CLI recording
# Install the machine-level CLI
uv tool install mergetrain # or: pipx install mergetrain
codex plugin marketplace add yongjip/mergetrain --ref main codex plugin add mergetrain@mergetrain
agy plugin install https://github.com/yongjip/mergetrain
For VS Code / GitHub Copilot or direct MCP setup, see the MCP installation and deployment-confirmation guide.
Initialize the repository:
cd /path/to/your/repo
mergetrain init --project my-app --write
Add at least one project gate to .mergetrain.yaml. A new configuration has gates: [], so it runs no project tests. For a Python project that uses pytest:
gates:
Use test commands for your project. Gates must leave the assembled checkout unchanged. init also creates AGENTS.mergetrain.md and CLAUDE.mergetrain.md. Link them from your existing AGENTS.md or CLAUDE.md. Commit and land the configuration and instructions through your normal integration path before creating task worktrees.
After the task agent commits a clean branch in its own worktree:
mergetrain status --json
mergetrain enqueue \ --task "add health check" \ --branch agent/health
The task agent stops after enqueueing. From the operator checkout, run these commands when validation and deployment are authorized:
mergetrain status
mergetrain deploy
For long-running gates, run mergetrain validate earlier; it never pushes and leaves one exact train Ready for the later deploy confirmation.
deploy names the configured atomic Git ref update; it does not imply an App Store, Kubernetes, or other provider release.
Agents commit and enqueue. One runner owns merge → test → push → verify. Unattended daemons process only jobs that a human explicitly enqueued with --auto. For manual jobs, daemon --validate-only can run merge and gates in the background, but it pauses at the validated-train approval boundary and never pushes.
See the quickstart for configuration, daemon, and multi-repository Hub setup.
Use a Git worktree merge queue when parallel Claude Code sessions or parallel Codex worktrees produce committed branches in the same repository. The plugin install guide connects either client to the queue. Task agents commit, enqueue, and stop. A separately authorized runner tests the combined branches and handles the push.
For Orca-managed worktrees, see the Orca setup and queue guide for tested terminal commands, shared queue behavior, validation, and repair. The Orca agent guide adds native Codex, Claude Code,
只显示了开头部分;其余内容请在仓库中阅读