# Agent Intern

Connects external CLI tools like Gemini, Codex, and Copilot as sub-agents inside Claude Code. Offload routine edits and preserve your primary token limits.

- MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 29
- Author: SinanTufekci
- License: MIT · policy=link-only · description only; the file stays with the author
- Source: https://github.com/SinanTufekci/agent-intern
- Updated: 2026-10-15
- HTML: https://affpapa.org/en/nevibecode/mcp/agent-intern

## What it does

The server exposes existing command-line AI tools as callable functions inside Claude Code. It routes tasks to Gemini via `agy`, ChatGPT via `codex`, GitHub Copilot, or Cursor. You do not need dedicated server API keys because the bridge relies on the active logins from your installed CLI sessions. If you lack paid subscriptions, running the `opencode-ai` utility provides free models without credentials.

Parallel execution handles multiple errands at once. Tooling like `agent_swarm` runs concurrent tasks across different engines, while built-in routines request second opinions from competing model families to spot blind spots in diffs. Gemini handles graphic creation, saving files straight into the workspace.

The server will not launch via `uvx` unless you have `uv` installed locally. You also need at least one supported CLI pre-installed and authenticated on your machine. Passing `watch=true` pops open a live step-by-step progress monitor.

## Requirements
- Needs: Python and uv (commands run via uvx)

## Install

### Claude Code (native platform)

**Platform CLI**
```bash
claude mcp add agent-intern -- uvx agent-intern
```
uvx runs the command named after the package; if the README names another one, use uvx --from agent-intern <command>

### Codex

**Platform CLI**
```bash
codex mcp add agent-intern -- uvx agent-intern
```
uvx runs the command named after the package; if the README names another one, use uvx --from agent-intern <command>

### Cursor

**Config file**
File `.cursor/mcp.json`:
```json
{
    "mcpServers": {
        "agent-intern": {
            "command": "uvx",
            "args": [
                "agent-intern"
            ]
        }
    }
}
```
uvx runs the command named after the package; if the README names another one, use uvx --from agent-intern <command>

### GitHub Copilot

**Config file**
File `.vscode/mcp.json`:
```json
{
    "servers": {
        "agent-intern": {
            "type": "stdio",
            "command": "uvx",
            "args": [
                "agent-intern"
            ]
        }
    }
}
```
uvx runs the command named after the package; if the README names another one, use uvx --from agent-intern <command>

### Gemini CLI

**Platform CLI**
```bash
gemini mcp add agent-intern uvx agent-intern
```
uvx runs the command named after the package; if the README names another one, use uvx --from agent-intern <command>

## When to use it
- hand off diff reviews to competing model families
- generate graphics via Gemini directly into project folders
- process batches of source files concurrently using swarms
- cut Claude token burn by running chores through secondary CLIs

## Example prompts
- Ask Gemini to draw a logo for the docs and place it into `assets/`.
- Inspect the latest git diff using Copilot and highlight disagreements.
- Run a parallel swarm to summarize every file inside `src/handlers`.

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md