> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-codexf-1788227809-773f4d5.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Define a Managed Deep Agent

> Configure the model and core capabilities of a Managed Deep Agent.

The agent definition selects the model and core capabilities of a Managed Deep Agent.

<Note>
  Managed Deep Agents is in **public [beta](/langsmith/release-stages)** and available on [LangSmith Cloud](/langsmith/cloud) in the US region only.
</Note>

## Project structure

The agent entry lives at the project root:

```text theme={null}
my-agent/
  agent.ts
```

Export the agent definition as a named `agent`. You can also use `agent.tsx`.

## Define an agent

Use `defineDeepAgent`:

<CodeGroup>
  ```ts OpenAI theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "openai:gpt-5.5",
  });
  ```

  ```ts Anthropic theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "anthropic:claude-sonnet-4-6",
  });
  ```

  ```ts Google Gemini theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "google-genai:gemini-3.6-flash",
  });
  ```
</CodeGroup>

| Parameter                              | What it does                                                          |
| -------------------------------------- | --------------------------------------------------------------------- |
| [`name`](#name)                        | Sets the agent and default deployment name                            |
| [`model`](#model)                      | Selects the chat model                                                |
| [`tools`](#tools)                      | Adds tools the agent can call                                         |
| [`middleware`](#middleware)            | Adds behavior around model calls, tool calls, and the agent lifecycle |
| [`subagents`](#subagents)              | Defines specialized agents for delegated tasks                        |
| [`permissions`](#permissions)          | Controls path-level access for filesystem tools                       |
| [`interruptOn`](#human-in-the-loop)    | Pauses before selected tool calls for human approval                  |
| [`responseFormat`](#structured-output) | Defines a structured output schema                                    |

## Name

`name` is required. Pass a static string that starts with a letter and contains only letters, numbers, underscores, or hyphens, such as `"research-assistant"`.

Managed Deep Agents uses the name as the LangGraph assistant ID and the default LangSmith deployment name. You can override the deployment name with `mda deploy --name` without changing the agent definition.

## Model

Set `model` to the chat model the agent uses. The simplest option is a `provider:model` string. Add the provider's API key to `.env` so the model works locally and in the deployment.

<CodeGroup>
  ```ts OpenAI theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "openai:gpt-5.5",
  });
  ```

  ```ts Anthropic theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "anthropic:claude-sonnet-4-6",
  });
  ```

  ```ts Google Gemini theme={null}
  import { defineDeepAgent } from "managed-deepagents";

  export const agent = defineDeepAgent({
    name: "research-assistant",
    model: "google-genai:gemini-3.6-flash",
  });
  ```
</CodeGroup>

Pass a LangChain chat model instance instead when you need to configure model parameters in code. For model options and supported providers, see [Models](/oss/javascript/deepagents/models).

### Use LLM Gateway

You can use [LLM Gateway](/langsmith/llm-gateway) to apply rate limits, fallbacks, and other policies to model calls.

Prefix the gateway model ID with `langsmith:`:

```ts theme={null}
import { defineDeepAgent } from "managed-deepagents";

export const agent = defineDeepAgent({
  name: "my-agent",
  model: "langsmith:moonshotai/kimi-k3",
});
```

<Note>
  Gateway model IDs use a slash between provider and model (`langsmith:provider/model-name`). Model strings that call a provider directly use a colon (`provider:model-name`).
</Note>

The gateway routes each request by model ID. `moonshotai/kimi-k3` is a LangChain-hosted model, so it requires no provider secret and draws on [Gateway Credits](/langsmith/llm-gateway-credits). A model ID that starts with a provider your workspace has configured, such as `anthropic/claude-opus-5`, uses that [provider secret](/langsmith/llm-gateway-admin-setup#1-add-provider-secrets) and bills to your own provider account.

For more information, see [LLM Gateway](/langsmith/llm-gateway).

## Tools

Pass tools in the `tools` array to let the agent call application logic or external services.

Define tools in local modules, import them into the agent entry, and add them to the definition. See [Custom tools](/langsmith/javascript/managed-deep-agents-tools). To add tools from remote MCP servers without importing them into the agent entry, use [MCP connectors](/langsmith/javascript/managed-deep-agents-mcp-connectors).

## Middleware

Pass middleware in the `middleware` array to add behavior around model calls, tool calls, and the agent lifecycle. Middleware runs in array order.

See [Custom middleware](/langsmith/javascript/managed-deep-agents-middleware).

## Subagents

Pass subagent definitions in `subagents` when the agent should delegate specialized or context-heavy work. Each subagent can have its own prompt, model, and tools. See [Subagents](/oss/javascript/deepagents/subagents).

## Permissions

Pass filesystem permission rules in `permissions` to control which paths the agent's built-in filesystem tools can read or write. See [Permissions](/oss/javascript/deepagents/permissions).

## Human-in-the-loop

Set `interruptOn` to pause before selected tool calls.

Use this for actions that require a person to approve, edit, or reject the call before it runs. See [Human-in-the-loop](/langsmith/javascript/managed-deep-agents-tools#human-in-the-loop).

## Structured output

Set `responseFormat` when the agent must return data that matches a schema instead of an unconstrained text response.

See [Structured output](/oss/javascript/langchain/structured-output).

Configure the system prompt, skills, memory, sandbox, identity, channels, and schedules through their project files rather than the agent definition. See [Project structure](/langsmith/javascript/managed-deep-agents-project-structure).

***

<div className="source-links">
  <Callout icon="terminal-2">
    [Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
  </Callout>

  <Callout icon="edit">
    [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/langsmith/managed-deep-agents-agent-definition.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>
</div>