REA
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Description from the maker (original English)
Delegate from Claude Code to Gemini, Codex, Copilot, Cursor and opencode CLIs as sub-agents.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
Passed 2/2 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Python (uv)
SettingsDeveloperEdit Config
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}Use Agent Intern and tell me what you can do for me, then show me one thing✓ If Claude says it is using Agent Intern or shows a Agent Intern tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Agent Intern yet
Agent Intern runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Agent Intern
B · Others in Developer tools that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add agent-intern -- uvx agent-internYou should see Agent Intern listed as connected
Use Agent Intern and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Agent Intern or shows a Agent Intern tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Use Agent Intern and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Agent Intern or shows a Agent Intern tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Use Agent Intern and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Agent Intern or shows a Agent Intern tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Claude Code
claude mcp add agent-intern -- uvx agent-internClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"agent-intern": {
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"agent-intern": {
"type": "stdio",
"command": "uvx",
"args": [
"agent-intern"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
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 11, 2026
The registry name was verified with the GitHub account SinanTufekci, which owns the repo
Code last changed 2 days ago
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 2 of 2 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed 2 days ago, and the latest version (0.36.0) reached the registry 2 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: REA, Netdata, Front-End Checklist
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Reverse engineer anything from your terminal or agent with one CLI and MCP server.
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Review frontend code and live pages against 386 quality-gated web development rules.
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.
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