Core concepts
Prerequisites
- A reachable OMA deployment
- An API key
Install the CLI
- Homebrew (macOS)
- curl (Linux/WSL)
- Go
Install the SDK
- Python
- TypeScript
- Java
- Go
- C#
- Ruby
- PHP
Create your first session
Managed Agents API requests require the
managed-agents-2026-04-01 beta header, except memory store endpoints, which use agent-memory-2026-07-22 instead. The SDK sets the correct beta header automatically. See Beta headers.1
Create an agent
Create an agent that defines the model, system prompt, and available tools.The
agent_toolset_20260401 tool type enables the full set of pre-built agent tools (bash, file operations, web search, and more). See Tools for the complete list and per-tool configuration options.Save the returned agent.id. You’ll reference it in every session you create.2
Create an environment
An environment defines the sandbox where your agent runs.Save the returned
environment.id. You’ll reference it in every session you create.3
Start a session
Create a session that references your agent and environment.
4
Send a message and stream the response
Open a stream, send a user event, then process events as they arrive:The agent writes a Python script, runs it in the sandbox, and verifies the output file was created. Your output looks similar to this:
What’s happening
When you send a user event, Open Managed Agents:- Provisions a sandbox: Your environment configuration determines how it’s built.
- Runs the agent loop: The agent determines which tools to use based on your message.
- Runs tools: File writes, bash commands, and other tool calls run inside the sandbox.
- Streams events: You receive real-time updates as the agent works.
- Goes idle: The agent emits a
session.status_idleevent when it has nothing more to do.
Build a complete app
Each of these quickstarts pairs Open Managed Agents with a popular chat framework to make a complete, runnable application. In each one, the framework renders the chat surface while a managed session runs the agent loop server-side: the session holds the transcript, runs tools in a sandbox, and streams events that the front end renders.Chat SDK
A research analyst in a browser chat built with Vercel’s Chat SDK. Each conversation is one persistent session that streams its reply while a live feed shows the tool calls. Swapping the Chat SDK adapter moves the same handler to Slack, Teams, Discord, or WhatsApp.
assistant-ui
A spreadsheet analyst in a chat built from assistant-ui primitives. Sessions are the thread list, one reducer turns the session event log into messages and tool cards, and each bash command renders an inline Allow/Deny gate before it runs.
CopilotKit (AG-UI)
A personal finance assistant in a CopilotKit chat. The AG-UI adapter for Open Managed Agents maps each chat thread to a managed session and streams replies token by token, and custom tools render interactive charts inline in the conversation.
Next steps
Define your agent
Create reusable, versioned agent configurations
Configure environments
Customize networking and sandbox settings
Agent tools
Enable specific tools for your agent
Session event stream
Handle events and steer the agent mid-execution
Scheduled deployments
Run your agent on a recurring cron schedule
Knowledge wiki quickstart
Distill a document corpus once into a knowledge wiki, then answer repeated questions from it at a fraction of the cost