Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Delegate from Claude Code to Gemini, Codex, Copilot, Cursor and opencode CLIs as sub-agents.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add agent-intern -- uvx agent-internPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"agent-intern": {
"type": "stdio",
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub SinanTufekci, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.34.0) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Rystic
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Start, seed, clock, inspect and diff Rystic API simulators from your agent.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo