The Terraform for AI agents. Define your team once, deploy to Claude Code, OpenClaw, Cursor, Codex, Gemini, Copilot, Kiro. Declarative language (.at files) + Claude Code skill + interactive visualizer.
<h1 align="center">AgenTopology</h1> <p align="center"> <strong>The Terraform for AI agents.</strong><br/> Define your agent team once. Deploy to any platform. </p> <p align="center"> <a href="https://agentopology.com"><img src="https://img.shields.io/badge/website-agentopology.com-purple" alt="website" /></a> <a href="https://www.npmjs.com/package/agentopology"><img src="https://img.shields.io/npm/v/agentopology" alt="npm" /></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-Apache%202.0-blue" alt="license" /></a> </p> <p align="center"> <strong>Claude Code</strong> · <strong>OpenClaw</strong> · <strong>Codex</strong> · <strong>Cursor</strong> · <strong>Cursor CLI</strong> · <strong>Cursor</strong> · <strong>Kiro</strong> </p> <p align="center"> <em>Ships with a Claude Code skill — just type <code>/agentopology</code> and describe your team.</em> </p> <br/> ## The Problem Building one AI agent is easy. Building a **team** of agents that actually works together is brutal. You want a marketing team? A dev pipeline? A support squad? You spend hours wiring up AGENT.md files, soul.md configs, MCP servers, hooks, and scripts. You get it working in Claude Code. Then you need the same team in OpenClaw — and you start from scratch. Different config format. Different directory structure. Different conventions. Same agents, same logic, zero portability. **OpenClaw alone** needs soul.md, skill files, channel configs, gateway setup, and workspace definitions — for each agent. Multiply that by 5 agents and you're maintaining 20+ files that you can't visualize, validate, or hand off to anyone. And that's just the platform problem. The architecture problem is worse: - **How do you see the big picture?** Your topology is scattered across 15 files in nested directories. No diagram. No single source of truth. - **How do agents talk to each other?** You hack together file-based protocols or copy-paste context between prompts. There's no sta
Agent that generates comprehensive documentation, API references, architecture diagrams, and developer onboarding guides from existing code.
Agent configuration for systematic bug investigation that traces issues from error logs through the codebase to root cause with suggested fixes.
Agent for integrating third-party APIs including SDK setup, type generation, error handling, retry logic, and rate limit management.
Cursor's built-in autonomous coding agent that can make multi-file edits, run terminal commands, search the codebase, and iteratively build features with minimal human intervention.
Cloud-based autonomous coding agent that runs in the background on remote sandboxed environments, handling complex multi-step tasks while you continue working.
Cursor's multi-file editing agent within Composer mode that can create, edit, and delete files across your entire project in a single conversation.