Public betaTypeScript agent SDK + coding CLI

One foundation for agents you use and agents you build.

Build an agent into your TypeScript application with the SDK. Or work in your terminal with the coding CLI built from the same public components. Configure a model endpoint, tools, permissions, and sessions for the task at hand.

Public packages · Node.js 22.12 or later · Bring a model endpoint

Our direction: agents that can reliably advance the systems they are built on.

01 / The shared foundation

Inspect the pieces. Then run a first query.

The agent framework assembles sessions, tools, and permission checks. The coding CLI is one maintained interface built on it. You can use the framework from your own Node.js application.

@robota-sdk/agent-frameworkAgent frameworksessions · tools · permissions
@robota-sdk/agent-cliCoding CLIrobota
One public TypeScript foundation, with an embeddable path and a ready terminal interface.
Install the SDK packages
npm install @robota-sdk/agent-framework @robota-sdk/agent-provider-openai
One-shot TypeScript query
import { createQuery } from '@robota-sdk/agent-framework';
import { OpenAIProvider } from '@robota-sdk/agent-provider-openai';

const model = 'your-loaded-model-id';
const query = createQuery({
  provider: new OpenAIProvider({
    apiKey: 'local',
    baseURL: 'http://127.0.0.1:1234/v1',
  }),
  model,
});

try {
  console.log(await query('Reply with one sentence.'));
} finally {
  await query.shutdown();
}

This static example requires a running OpenAI-compatible server and a model ID loaded there. The local port is illustrative. The 'local' API key is a placeholder for servers without authentication; replace it with your server's credential if required. A published-package loopback check verified the SDK call and cleanup; no real model answer is shown.

Inspect the framework source

02 / Coding CLI

CLI setup outline
npx @robota-sdk/agent-cli

You need Node.js 22.12+ and an API key or a running local model server. Provider costs and policies depend on the endpoint you choose.

After configuring a provider and model, type a normal prompt:

Reply with one sentence.

Look for a text reply from the selected model; its wording and quality depend on that model. Before asking about project files, decide whether to trust the workspace.

Read CLI setup

02 / Choose a first task

Two practical ways in.

01

Build a query into your app

Install the framework and a provider adapter, then call createQuery from a Node.js script. Move to InteractiveSession when your own UI needs a longer conversation.

Before you run it

You need Node.js 22.12+, a configured provider endpoint, and a model ID. The example on this page uses a running local OpenAI-compatible server.

Read the SDK guide
02

Ask the coding CLI about a project

Run the CLI, configure a provider and model with a hosted key or running local endpoint, then decide whether to trust the workspace before project context is loaded.

Before you run it

You need Node.js 22.12+ and an API key or a running local model server. Provider costs and policies depend on the endpoint you choose.

Read CLI setup

03 / What you can configure

Controls at the boundary where they matter.

01

Model endpoints

Inject a provider adapter for Anthropic or OpenAI-compatible endpoints; local servers need their own running model. Models and provider terms vary by setup.

Provider guide
02

Tools and permissions

Use file, shell, and web tools with an explicit permission mode. In an unattended default-mode query, requests needing approval are denied unless a handler answers them.

Permission guide
03

Sessions

InteractiveSession handles turns and events. Persistence and resume need a session store supplied by the host; createQuery does not save a session by default.

Session guide
04

MCP connections

MCP support is available through separate transport and client components. Configure and authorize each connection before relying on its tools.

MCP guide

04 / Know the fit

Use the source. Understand the terms.

A public codebase lets you inspect how the SDK and CLI are assembled. Start with the package and source that match your task.

Explore the showcase

Open source and commercial paths

The code is offered under AGPL-3.0, with a commercial licensing path for uses that need different terms. Review the license for your distribution or service.

Provider costs are separate

The SDK and CLI do not include model inference. A hosted provider can charge for usage; local inference has its own compute and operating costs.

First-party showcase

The coding CLI is the maintained example of these public components composed into a developer tool. Browse its source and the current showcase.

05 / Direction, not a guarantee

Our agents develop and advance our agents.

That is the long-term direction of the project. Today, the usable foundation is an SDK and coding CLI with explicit providers, tools, and host decisions. Reliable autonomous self-development must be demonstrated through actual outcomes as the system evolves.

06 / Before you start

Common questions.

Do I need the CLI to use the SDK?

No. Import the agent framework into your own Node.js host and inject a provider. The CLI is one complete interface built from public components.

Will a query run without configuring a model?

You need a provider endpoint and a suitable model. A local OpenAI-compatible example requires its server and model to be running; a hosted provider needs its own credentials and terms.

Does the SDK persist conversations automatically?

No. A simple createQuery call is not a durable session. Supply a session store when your host needs save and resume behavior.

What should I read before enabling tools?

Review project trust and permission modes. In default mode, an unattended request for approval is denied unless your host provides a permission handler.

Start with one real task.

Choose the embeddable query or set up the coding CLI. Both paths begin with the provider and access decisions you control.