Agent Intern

Name: Agent Intern
Author: SinanTufekci

by SinanTufekciversion 0.34.0i★ –iRuns on your computer

Registry nameio.github.SinanTufekci/agent-intern

Install

Overview

Description from the maker (original English)

Delegate from Claude Code to Gemini, Codex, Copilot, Cursor and opencode CLIs as sub-agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "agent-intern": {
      "command": "uvx",
      "args": [
        "agent-intern"
      ]
    }
  }
}

Run this in your terminal

claude mcp add agent-intern -- uvx agent-intern

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "agent-intern": {
      "command": "uvx",
      "args": [
        "agent-intern"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "agent-intern": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "agent-intern"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account SinanTufekci, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32545 servers in this category
Published to the registry more recently than 88% of the other 32545 servers in this category
Basic checks equal to or better than 100% of the other 32545 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Agent Intern safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.34.0) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Python MCP

Alternatives

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

agent-intern

Give Claude Code an intern.

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.

Quick start

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:

*"Ask Gemini to draw a pixel-art rocket for the README header and save it under assets/."*
*"Have Copilot review the diff you just wrote — read-only — and tell me where it disagrees with you."*
*"Summarise each of the six files in src/handlers in parallel with a swarm."*

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 *_status call

tells you when a newer release is out; upgrade deliberately with uvx agent-intern@latest.

Other install paths, from source included →

What it's for

🎨 Images, inside Claude Code. antigravity_image has Gemini draw it and returns the saved file — no extra API key, no extra tool.
🧠 A second opinion. A different model family reviews what Claude just wrote. Their blind spots rarely overlap.
🐝 Parallel fan-out. agent_swarm runs N tasks at once and can mix backends in a single call (~2.8× at 3 Gemini workers).
⚖️ Ready-made panels. 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.
💸 Cheaper grunt work. Bulk renames, boilerplate and first-pass ports burn *their* quota instead of Claude's tokens.
🆓 No subscription? Still works. opencode's free models answer with zero credentials — slow, but free.
🔌 Zero new auth. Piggybacks the CLI logins you already have. The bridge manages no keys of its own.

Watch it work

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 →

Ready-made panels

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 →

Backends

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

verification issue

— about a minute: call grok_ask("say hi") or muse_ask("say hi") — is the most useful

contribution you can make.

Details →

How it works

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

Only the beginning is shown; read the rest in the repo

Agent Intern

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Python MCP

README from the maker

agent-intern

Give Claude Code an intern.

Quick start

What it's for

Watch it work

Ready-made panels

Backends

How it works