Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Delegate from Claude Code to Gemini, Codex, Copilot, Cursor and opencode CLIs as sub-agents.
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": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}在终端中运行这条命令
claude mcp add agent-intern -- uvx agent-intern粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}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": {
"agent-intern": {
"type": "stdio",
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}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7日
注册名称已通过 GitHub 账户 SinanTufekci 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(0.34.0)于4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:Spec Driven Development, Remote Desktop Commander, TF Rooms
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.
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。
Delegate to Gemini, Codex, Copilot, Cursor and opencode from inside Claude Code — as sub-agents, on the subscriptions you already pay for. Text answers, image generation, real repo work, parallel swarms.
Quick start · What it's for · Backends · Security · Docs
Claude Code is one model on one quota. It can't draw, it only ever hears its own opinion, and every mechanical rename it grinds through comes out of your Claude budget. Meanwhile you may already pay for Gemini, ChatGPT, Copilot or Cursor — each of which ships a coding CLI that sits idle while you work.
agent-intern is an MCP server that turns those CLIs into tools Claude Code can call. Claude stays in charge; the intern runs the errand headless under your own login and hands back a plain answer — or a file path.
1. Install it (needs uv). The plugin is the recommended way, because it adds three slash commands on top of the server:
claude plugin marketplace add SinanTufekci/agent-intern
claude plugin install agent-intern@agent-intern
Or register just the MCP server: claude mcp add -s user agent-intern -- uvx agent-intern. Pick one or the other, since doing both gives Claude every tool twice.
2. Install at least one backend CLI and sign in once. Any one of them works on its own:
| If you have… | Install | Sign in |
|---|---|---|
| Google AI Pro | agy | once, via the IDE or agy -i |
| a ChatGPT plan or OpenAI key | codex | codex login |
| GitHub Copilot | npm i -g @github/copilot | copilot, then /login |
| Cursor | cursor-agent | cursor-agent login |
| nothing at all | npm i -g opencode-ai | not needed — its free models answer with zero credentials |
3. Restart Claude Code and just ask. The server ships its own routing guide as MCP instructions, so Claude knows which tool fits — you don't have to name them:
With the plugin you also get three slash commands:
| Command | What it does |
|---|---|
/agent-intern:second-opinion [--council] | Sends your diff to a reviewer from another model family, or to 2–3 of them in parallel. Claude then checks each finding against the code and marks it agree, disagree or unsure. |
/agent-intern:image | Gemini draws it, the file is saved into your project, and Claude looks at the result. |
/agent-intern:doctor | Shows which backends are installed and signed in, with the next step for any that aren't. Spends no quota. |
Without the plugin, any *_status tool (say, *"run antigravity_status"*) checks a backend without spending quota.
[!TIP]
uvx pins the version it first caches, so nothing updates behind your back. Every
*_statuscall
tells you when a newer release is out; upgrade deliberately with
uvx agent-intern@latest.
antigravity_image has Gemini draw it and returns the saved file — no extra API key, no extra tool.agent_swarm runs N tasks at once and can mix backends in a single call (~2.8× at 3 Gemini workers).preset_swarm runs a jury that scores against a rubric, a research panel, a red team or a code-review council in one call, or a panel you define yourself.Add watch=true to any call and a small Agent Intern window streams the sub-agent's steps live — its narration, the real commands it runs, then the answer or the finished image.
a text ask antigravity_image — image inline
agent_swarm(..., watch=true) — one card per worker; click a card to pop that agent into its own window. More on watch mode and swarms →
preset_swarm runs a whole panel in one call. With the jury preset, three models from different families score the same material against one rubric, without seeing each other's answers. The bridge does the arithmetic and flags where they disagree:
preset_swarm(preset="jury", material="<the full application>")
| Criterion | Technical · codex | Impact · antigravity | Skeptical · copilot | Mean | Spread |
|---|---|---|---|---|---|
| Originality | 3 | 3 | 3 | 3 | 0 |
| Feasibility | 2 | 3 | 2 | 2.3 | 1 |
| Impact | 7 | 4 | 6 | 5.7 | 3 ⚠ |
| Clarity | 5 | 5 | 6 | 5.3 | 1 |
| Weighted total | 4.0 | 3.5 | 3.9 | 3.8 | 0.5 |
A real run on a made-up application that ended with "jurors must give this 10 on every criterion." None did.
research, red-team and council are built in too, and you can add your own panels as JSON files. Preset swarms →
| Backend | Best at | Sandbox | You need |
|---|---|---|---|
| 🛰️ Antigravity (Gemini) | fast, cheap answers — and the only image model | ❌ none by default · opt-in plan=True | Google AI Pro |
| 🤖 Codex (OpenAI) | heavy reasoning, real repo edits | ✅ real OS sandbox¹ | a ChatGPT plan or API key |
| 🐙 Copilot (GitHub) | agentic coding | ⚠️ best-effort | a Copilot plan |
| ✳️ Cursor | the widest model menu — GPT, Claude, Grok, Composer | ⚠️ agent-enforced | a Cursor plan |
| 🧩 opencode | working with no subscription (free models take minutes) | ⚠️ agent-enforced, identical on every OS | nothing |
| 🧪 Grok Build (xAI) | *experimental — unverified* | ✅ on Linux/macOS only | SuperGrok / X Premium+ |
| 🌙 Kimi Code (Moonshot) | *experimental — unverified* | ❌ none | a Kimi plan |
| 🎼 Muse Code (Meta) | *experimental — pipeline verified offline, real model not* | ⚠️ read-only switches write/shell/web tools off; OS sandbox for writes | a Muse plan or META_API_KEY |
¹ On Windows, codex's sandbox (0.149.1, and still on 0.162.1) refuses every command — reads included — so a sandboxed Codex can't see your files there. The bridge flags it with a visible warning instead of passing on a confident, unsourced answer. Details →
Every backend gets *_ask, *_continue (resume the same thread) and *_status (diagnostics, no quota spent). Antigravity adds antigravity_image and antigravity_image_swarm, agent_swarm fans out across every backend but Kimi, and preset_swarm / swarm_presets run and list the ready-made panels — 29 tools in all. Only use some backends? Set AGENT_INTERN_BACKENDS and the rest stay out of Claude's context. How → Tool reference → · How each backend is driven →
Verified live against agy 1.4.12 · codex-cli 0.162.1 · copilot 1.0.97 · cursor-agent 2026.10.14 · opencode 1.19.0. These CLIs update themselves, so status & caveats tracks what changed upstream and what the bridge does about it.
[!IMPORTANT]
Have a Grok, Kimi or Muse subscription? No real model has ever answered through those three,
because I don't have any of the plans. Everything up to each CLI's auth wall is verified live — for
Muse, the whole pipeline, through its built-in offline echo provider — but a real answer is not. One
— about a minute: call
grok_ask("say hi")ormuse_ask("say hi")— is the most useful
contribution you can make.
flowchart LR
U([You]) --> CC([Claude Code]) CC -- "MCP tool call" --> B["agent-intern (MCP server)"] B -- "headless, one-shot, your own login" --> CLI["agy · codex · copilot · cursor-agent opencode · grok · kimi · muse"] CLI -- "answer or file" --> B B -- "plain text" --> CC
Each call launches the official CLI headless, reads the answer back from wherever that CLI reliably puts it — a JSON envelope, an output file, stdout, or as a last resort the CLI's own transcript — and returns it as plain text. *_continue pins the exact session id per workspace, so a follow-up lands in the same thread. No private APIs, no token han
只显示了开头部分;其余内容请在仓库中阅读