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)
Hand tasks from Claude Code, Codex or any MCP client to a local DeepSeek Harness.
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": {
"dsh-baton": {
"command": "npx",
"args": [
"-y",
"dsh-baton-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add dsh-baton -- npx -y dsh-baton-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"dsh-baton": {
"command": "npx",
"args": [
"-y",
"dsh-baton-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": {
"dsh-baton": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"dsh-baton-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9日
注册名称已通过 GitHub 账户 JialaoLiu 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(0.6.10)于今天进入注册中心。
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 Node.js。
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:↓ 每周下载量i★ 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
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。
English | 中文 · macOS · Windows ( guide ) · no Node.js needed · zero dependencies · MIT
Quick start · See it run · Token usage · How it works · Tools · Security
Hand coding tasks from Claude Code or Codex to DeepSeek Harness on your machine: the task runs live in the Harness window, the main agent hears back once when it ends, and it gets back the files that changed, the project's own test results and a requirement-by-requirement checklist.
Needs DeepSeek Harness ≥ 0.2.1-rc.2 (signed in) and Claude Code or Codex. Quick start →
dsh-baton is an MCP server plus a small Harness plugin. The main agent hands the task to an ordinary Harness session with one tool call: you watch it run in the Harness window and can step in at any time, and the main agent hears back once, without polling. Unlike a plain MCP bridge to another model, the work stays visible and the proof comes back with the result.
Beyond the savings, the split itself helps:
Nothing else to install: no Node.js, no terminal. The steps are the same on macOS and Windows.
1. Add the plugin in Harness: Plugins (插件) → Add plugin (添加插件) → type dsh-baton-host → Install (安装) → Enable now (立即启用).
Switched on, the plugin registers dsh-baton for Claude Code and Codex, for every folder, and Harness says so.
2. Open a new chat: in Claude Code or Codex, start a new conversation; one that was already open does not see dsh-baton yet. The steps are the same for both. Codex asks you to approve MCP tool calls: approve the dsh-baton tools (for unattended codex exec runs, add --approve-for-me).
3. Check: ask it to call dsh_list_workspaces. It lists your Harness workspaces.
That is all. To hand a task over, end the request with "hand it to DeepSeek Harness". Updating, removing, Windows, and registering by hand when the plugin could not, are further down.
New in 0.6.4: Codex waits in one dsh_wait call of up to 59 minutes, so a run that ends within the hour costs one model request to wait for, and the result arrives as an ordinary reply in the chat. Update the plugin in Harness and new Codex conversations have it, with no restart.
One Codex chat starts a task, queues a follow-up, steers the running turn, and waits for all three:
Codex and Claude take turns in the same Harness session, and every message is labelled with who sent it:
More demos →
In short: hand over the big, long jobs. With Claude Code the total cost, DeepSeek included, is 51–78% lower. With Codex on GPT-6 Astra it is 47–81% lower, and the long kanban app takes 16.01% of a ChatGPT Plus 5-hour window instead of 86.01%.
Hand it over: big jobs, long jobs, and whenever the 5-hour window is running low. The main agent's own spend drops 61–87% on every task and model.
Do it yourself: small tasks on Codex with GPT-6.1 Sol. Sol is cheap enough that DeepSeek's part of a hand-over, two thirds or more, outweighs what Sol saves.
The three test tasks, asked the way a user would (the requests are in Chinese, linked as written):
| Task 3 | Alone | Handed over |
|---|---|---|
| Opus 5.5 high | 55/55, 39 min | 55/55, 93 min |
| GPT-6.1 Sol high | 55/55, 18 min | 55/55, 101 min |
| GPT-6 Astra high | 55/55, about 31 min | 55/55, about 87 min |
Cost per task at list price, DeepSeek V4.1 Flash 1017 at its peak price. Opus 5.5 runs in Claude Code, GPT-6.1 Sol and GPT-6 Astra in Codex, all at high effort:
| Task | Model | Alone | Handed over: main agent | Handed over: DeepSeek | Handed over: total | Total | Main agent | 5-hour window, alone → handed over |
|---|---|---|---|---|---|---|---|---|
| Task 1 · CLI tool | Opus 5.5 high | $1.07 | $0.42 | $0.10 | $0.52 | −51.2% | −60.8% | — |
| GPT-6.1 Sol high | $0.17 | $0.06 | $0.13 | $0.20 | +15.3% | −62.9% | 2.08% → 0.77% | |
| GPT-6 Astra high | $0.79 | $0.30 | $0.12 | $0.42 | −47.4% | −62.0% | 7.83% → 2.98% | |
| Task 2 · Web app | Opus 5.5 high | $2.13 | $0.47 | $0.13 | $0.60 | −71.7% | −77.7% | — |
| GPT-6.1 Sol high | $0.41 | $0.06 | $0.18 | $0.25 | −40.2% | −84.5% | 5.08% → 0.79% | |
| GPT-6 Astra high | $2.27 | $0.30 | $0.13 | $0.42 | −81.4% | −86.9% | 22.43% → 2.94% | |
| Task 3 · Kanban app (phased) | Opus 5.5 high | $14.18 | $2.32 | $0.84 | $3.16 | −77.7% | −83.6% | — |
| GPT-6.1 Sol high | $1.12 | $0.22 | $0.81 | $1.03 | −8.1% | −80.5% | 13.71% → 2.67% | |
| GPT-6 Astra high | $8.69 | $1.62 | $0.74 | $2.35 | −72.9% | −81.4% | 86.01% → 16.01% |
What was tested, and how
dsh_wait call does it, also in one model request for every 59 minutes of a run.<img src="./assets/readme/en/architecture.gif" width="100%" alt="MCP clients call dsh-baton-mcp over stdio; it reaches the dsh-baton-host plugin inside Harness through an owner-only local socket; the
只显示了开头部分;其余内容请在仓库中阅读