# Overview



Managed Agents is Clusterbase's runtime for **autonomous AI agents**. You define an
agent once — a model, a system prompt, a set of tools — and then run it however
you need: interactively, on a cron schedule, in response to a GitHub event, or as
a one-off job in a fresh VM.

Agents run on the managed-agents service at **`https://agents.clusterbase.dev`**.
You can drive everything two ways:

* **The [Console](https://console.clusterbase.ai)** — a visual agent builder,
  agent editor, session transcripts, schedules, and triggers. The fastest way to
  get started.
* **The HTTP API** — the same capabilities over a REST API, for building agents
  into your own products and pipelines. See the [API reference](/docs/agents/api-reference).

## The model [#the-model]

Three objects make up the system. Understanding how they relate is most of the
mental model:

| Object      | What it is                                                                                                                            |
| ----------- | ------------------------------------------------------------------------------------------------------------------------------------- |
| **Agent**   | A reusable, versioned configuration: name, model, system prompt, tools, MCP servers, reasoning effort, and an optional default VM.    |
| **Session** | A single runtime instance of an agent. It holds the conversation, pins the agent version it was created with, and tracks token usage. |
| **Event**   | One message on a session's timeline — your input (`user.message`), the agent's output, tool calls, tool results, and status changes.  |

You create an **agent**, start a **session** on it, append a `user.message`
**event**, and the agent runs — emitting thinking, tool calls, and messages back
onto the session as events you can stream live. See [Concepts](/docs/agents/concepts)
for the full domain model.

## What you can do [#what-you-can-do]

* **[Build and configure agents](/docs/agents/agents)** — pick a model, write a
  system prompt, attach tools and MCP servers, and (optionally) give the agent a
  VM for shell and file access.
* **[Run agents interactively](/docs/agents/sessions-and-events)** — start a
  session, send messages, and stream the agent's reasoning, tool calls, and
  replies over SSE.
* **[Schedule runs](/docs/agents/schedules)** — fire an agent on a cron schedule
  in any timezone (e.g. publish a daily report every weekday at 9am).
* **[Trigger on GitHub events](/docs/agents/triggers)** — run an agent when a PR
  opens, or mention `@cluster-build review` in a PR for an instant code review.
* **[Launch on-demand runs](/docs/agents/runs)** — provision an ephemeral VM with
  your repos cloned, run the agent, and tear it down automatically.
* **[Provision environments](/docs/agents/environments)** — long-lived
  Firecracker VMs an agent's sessions execute inside.
* **[Store MCP credentials](/docs/agents/vaults-and-mcp)** — connect agents to
  remote MCP servers, with secrets held in encrypted vaults.

## Authentication [#authentication]

Every API request is authenticated with a **Bearer JWT** from
[Sign in with Cluster](/docs/ccp/oidc) (the same `accounts.clusterbase.ai` identity
used across the platform). Agents, sessions, schedules, triggers, environments,
and vaults are **owner-scoped**: you only ever see and act on the resources
created under your own identity. See [Authentication](/docs/agents/api-reference#authentication)
for details.

## Next steps [#next-steps]

Start with the [quickstart](/docs/agents/quickstart) to build your first agent in
a couple of minutes, then read [Concepts](/docs/agents/concepts) for the full
picture.