Agent App is the application that AI agents build, evolve, and operate. A collaboration space for humans and agents beyond chat, voice, and generative UI.
📦 npm · 📖 Spec · 🧩 Harness plugins · 🤝 Contribute
An Agent App is a complete, stateful application. It has its own frontend, backend, and database that humans use visually and agents use programmatically using CLI-walk. The agent is the developer, the operator, and the software vendor, while you own the code, the data, and the features.
An Agent App is tech-stack-agnostic (any stack works, given a matching A2App adapter) and harness-agnostic (every agent harness can use it through a plugin or skills). This repository makes it a standard:
- the Agent App Framework: provides tools for any agent harnesses to build their own Agent App
- the A2App protocol: bi-directional communication protocol between an agent and an agentic app
- the A2App adapter: connecting an Agent App to any tech stack
app + A2App adapter = Agent App
Three steps:
1. Install the CLI.
npm i -g agent-app-frameworkThis gives you and your AI agent two commands: agent-app (build, evolve, manage) and a2app (operate).
2. Connect it to your harness. Choose one of two routes. Both need the CLI from step 1.
Skills (works with any harness). Copy the framework skills into the folder where your harness loads SKILL.md skills:
agent-app skills --install <your-harness-skills-dir> # e.g. .claude/skillsPlugin (a deeper fit). A plugin adds the skills plus commands, and in some harnesses a panel to see and manage your apps. For example:
openclaw plugins install @craftos/agent-app-openclaw
openclaw plugins enable a2appType /agent-app build a CRM in chat, or open the Agent Apps tab in the Control UI and click New +. To show your apps inside that tab, set gateway.controlUi.embedSandbox: "trusted" in your OpenClaw config (otherwise it wouldn't work).
pi install npm:@craftos/agent-app-piType /agent-app build a CRM in Pi.
dsh plugin --profile web add @craftos/agent-app-dshIn the dsh web UI, click Agent Apps in the left sidebar and use New +, or ask the agent in chat to build an app.
For Claude Code, Hermes, CraftBot, and other harnesses, see harness-plugins/.
3. Describe what you want. Tell your harness the app you need: a CRM, a dashboard, an expense tracker, anything. It refines the requirement, builds a full application to the Agent App Building Standard, verifies it, and launches it. Your need changes? Just tell the agent to evolve the agent app.
That's it! You now have custom software that both you and your agent can use. Happy collaboration!
Everything the harness does runs through two commands (You can drive the full loop by hand, but it is recommended to let your agent runs it).
Operate — a2app is a walk: you name a place in the app and act where you land.
a2app <app> # the app's modules (start here)
a2app <app> planning cards # one entity: its fields and operations
a2app <app> planning cards <id> # one record, and what its state allows now
a2app <app> data cards create --title "Buy milk" --due tomorrow
a2app <app> --find invoice # search names, get locations
a2app <app> tasks next --wait 60000 # block until the app has work, claim it, print it<app> is a directory, a registered id/name, or an http(s) URL (a URL operates a remote app, with its identity verified and pinned).
Build & evolve — agent-app:
agent-app <dir> scaffold # framework files + ownership canon
agent-app <dir> validate # the validation + security gate
agent-app <dir> serve # launch via the manifest pipeline
agent-app <dir> dev / promote # safe-evolve: build on a hidden port, gate, promote with backup
agent-app <dir> bridge start # watch the app's task queue and trigger your harness
agent-app list # every app with its port and live statusA2App is how your agent communicates with an Agent App. Agent Apps are built to include a CLI, which is the primary way an agent uses them. The agent then performs a CLI-walk to navigate and use the Agent App.
What is the difference between MCP, A2A, A2UI, and A2App? Each protocol has its own job, we listed the difference here:
| Protocol | What it does |
|---|---|
| MCP | Connects AI apps to outside tools and data |
| A2A | Lets AI agents talk to each other |
| A2UI | Lets agents describe interfaces that apps render natively |
| A2App | Lets agents control a large-scale app |
Tokens are what an AI agent spends on every message. We compared the same task on the same app, once with MCP (one tool per action) and once with A2App.
- Loading what the app can do. MCP lists every action as a tool up front, so the list grows with the app: 4.7k tokens at 100 actions. A2App gives the agent one command of ~50 tokens, and the agent walks to what it needs.
- Finishing one task. For very small apps, MCP costs slightly less because it needs fewer steps. Past about ~20 actions, A2App pulls ahead: 7k tokens at 100 actions, against 18k for MCP.
Larger the app, better the token efficiency is for A2App
pnpm install && pnpm -r build && pnpm -r testThe normative contracts are the JSON Schemas in spec/; the conformance/ suite is how an implementation proves it conforms. To contribute, see CONTRIBUTING.md.
Yup. MIT