{

"title": "Run AI Coding Agents with Coder",

"description": "Learn how to run and secure agents in Coder",

"path": "./tutorials/ai-agents/README.md",

"state": ["early access"],

"children": [

{

"title": "Learn about coding agents",

"description": "Learn about the different AI agents and their tradeoffs",

"path": "./tutorials/ai-agents/agents.md"

},

{

"title": "Create a Coder template for agents",

"description": "Create a purpose-built template for your AI agents",

"path": "./tutorials/ai-agents/create-template.md",

"state": ["early access"]

},

{

"title": "Integrate with your issue tracker",

"description": "Assign tickets to AI agents and interact via code reviews",

"path": "./tutorials/ai-agents/issue-tracker.md",

"state": ["early access"]

},

{

"title": "Best practices \u0026 adding tools via MCP",

"description": "Improve results by adding tools to your agents",

"path": "./tutorials/ai-agents/best-practices.md",

"state": ["early access"]

},

{

"title": "Supervise agents via Coder UI",

"description": "Interact with agents via the Coder UI",

"path": "./tutorials/ai-agents/coder-dashboard.md",

"state": ["early access"]

},

{

"title": "Supervise agents via the IDE",

"description": "Interact with agents via VS Code or Cursor",

"path": "./tutorials/ai-agents/ide-integration.md",

"state": ["early access"]

},

{

"title": "Programmatically manage agents",

"description": "Manage agents via MCP, the Coder CLI, and/or REST API",

"path": "./tutorials/ai-agents/headless.md",

"state": ["early access"]

},

{

"title": "Securing agents in Coder",

"description": "Learn how to secure agents with boundaries",

"path": "./tutorials/ai-agents/securing.md"

}

]

},

AI Coding Agents such as [Claude Code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview), [Goose](https://block.github.io/goose/), and [Aider](https://github.com/paul-gauthier/aider) are becoming increasingly popular for:

- Protyping web applications or landing pages

- Researching / onboarding to a codebase

- Assisting with lightweight refactors

- Writing tests and documentation

- Small, well-defined chores

With Coder, you can self-host AI agents in isolated development environments with proper context and tooling around your existing developer workflows. Whether you are a regulated enterprise or an individual developer, running AI agents at scale with Coder is much more productive and secure than running them locally.


Coder is free and open source for developers, with a [premium plan](https://coder.com/pricing) for enterprises. You can self-host a Coder deployment in your own cloud provider.

- A [Coder deployment](../../install/) with v2.21.0 or later

- A Coder [template](../../admin/templates/) for your project(s).

- Access to at least one ML model (e.g. Anthropic Claude, Google Gemini, OpenAI)

- Cloud Model Providers (AWS Bedrock, GCP Vertex AI, Azure OpenAI) are supported with some agents

- Self-hosted models (e.g. llama3) and AI proxies (OpenRouter) are supported with some agents

<children></children>

There are several types of coding agents emerging:

- **Headless agents** can run without an IDE open and are great for rapid

prototyping, background tasks, and chat-based supervision.

- **In-IDE agents** require developers keep their IDE opens and are great for

interactive, focused coding on more complex tasks.

Headless agents can run without an IDE open, or alongside any IDE. They

typically run as CLI commands or web apps. With Coder, developers can interact

with agents via any preferred tool such as via PR comments, within the IDE,

inside the Coder UI, or even via the REST API or an MCP client such as Claude

Desktop or Cursor.

| Agent | Supported Models | Coder Support | Limitations |

|---------------|---------------------------------------------------------|---------------------------|---------------------------------------------------------|

| Claude Code ⭐ | Anthropic Models Only (+ AWS Bedrock and GCP Vertex AI) | First class integration ✅ | Beta (research preview) |

| Goose | Most popular AI models + gateways | First class integration ✅ | Less effective compared to Claude Code |

| Aider | Most popular AI models + gateways | In progress ⏳ | Can only run 1-2 defined commands (e.g. build and test) |

| OpenHands | Most popular AI models + gateways | In progress ⏳ ⏳ | Challenging setup, no MCP support |

[Claude Code](https://github.com/anthropics/claude-code) is our recommended

coding agent due to its strong performance on complex programming tasks.

Coding agents can also run within an IDE, such as VS Code, Cursor or Windsurf.

These editors and extensions are fully supported in Coder and work well for more

complex and focused tasks where an IDE is strictly required.

| Agent | Supported Models | Coder Support |

|-----------------------------|-----------------------------------|--------------------------------------------------------------|

| Cursor (Agent Mode) | Most popular AI models + gateways | ✅ [Cursor Module](https://registry.coder.com/modules/cursor) |

| Windsurf (Agents and Flows) | Most popular AI models + gateways | ✅ via Remote SSH |

| Cline | Most popular AI models + gateways | ✅ via VS Code Extension |

In-IDE agents do not require a special template as they are not used in a

headless fashion. However, they can still be run in isolated Coder workspaces

and report activity to the Coder UI.

- [Create a Coder template for agents](./create-template.md)

Coder templates should be pre-equipped with the tools and dependencies needed

for development. With AI Agents, this is no exception.

- A Coder deployment with v2.21 or later

- A [template configured for AI agents](./create-template.md)

- Since agents are still early, it is best to use the most capable ML models you

have access to in order to evaluate their performance.

- Set a system prompt with the `AI_SYSTEM_PROMPT` environment in your template

- Within your repositories, write a `.cursorrules`, `CLAUDE.md` or similar file

to guide the agent's behavior.

- To read issue descriptions or pull request comments, install the proper CLI

(e.g. `gh`) in your image/template.

- Ensure your [template](./create-template.md) is truly pre-configured for

development without manual intervention (e.g. repos are cloned, dependencies

are built, secrets are added/mocked, etc.)

> Note: [External authentication](../../admin/external-auth.md) can be helpful

> to authenticate with third-party services such as GitHub or JFrog.

- Give your agent the proper tools via MCP to interact with your codebase and

related services.

- Read our recommendations on [securing agents](./securing.md) to avoid

surprises.

Model Context Protocol (MCP) is an emerging standard for adding tools to your

agents.

Follow the documentation for your [agent](./agents.md) to learn how to configure

MCP servers. See

[modelcontextprotocol/servers](https://github.com/modelcontextprotocol/servers)

to browse open source MCP servers.

In internal testing, we have seen significant improvements in agent performance

when these tools are added via MCP.

- [Playwright](https://github.com/microsoft/playwright-mcp): Instruct your agent

to open a browser, and check its work by viewing output and taking

screenshots.

- [desktop-commander](https://github.com/wonderwhy-er/DesktopCommanderMCP):

Instruct your agent to run long-running tasks (e.g. `npm run dev`) in the

background instead of blocking the main thread.

- [Supervise Agents in the UI](./coder-dashboard.md)

- [Supervise Agents in the IDE](./ide-integration.md)

- [Supervise Agents Programmatically](./headless.md)

- [Securing Agents](./securing.md)

- A Coder deployment with v2.21 or later

- A [template configured for AI agents](./create-template.md)

Once you have an agent running and reporting activity to Coder, you can view

status and switch between workspaces from the Coder dashboard.



- [Supervise Agents in the IDE](./ide-integration.md)

- [Supervise Agents Programmatically](./headless.md)

- [Securing Agents](./securing.md)

This tutorial will guide you through the process of creating a Coder template

for agents.

- A Coder deployment with v2.21 or later

- A template that is pre-configured for your projects

- You have selected an [agent](./agents.md) based on your needs

It is best to create a separate template for AI agents based on an existing

template that has all of the tools and dependencies installed.

This can be done in the Coder UI:


We currently publish a module for Claude Code and Goose. Additional modules are

[coming soon](./agents.md).

- [Add the Claude Code module](https://registry.coder.com/modules/claude-code)

- [Add the Goose module](https://registry.coder.com/modules/goose)

Follow the instructions in the Coder Registry to install the module. Be sure to

enable the `experiment_use_screen` and `experiment_report_tasks` variables to

report status back to the Coder control plane.

The Coder dashboard should now show tasks being reported by the agent.


- [Integrate with your issue tracker](./issue-tracker.md)

- A Coder deployment with v2.21 or later

- A [template configured for AI agents](./create-template.md)

Once you have an agent running and reporting activity to Coder, you can manage

it programmatically via the MCP server, Coder CLI, and/or REST API.

Power users can configure [Claude Desktop](https://claude.ai/download), Cursor,

or other tools with MCP support to interact with Coder in order to:

- List workspaces

- Create/start/stop workspaces

- Run commands on workspaces

- Check in on agent activity

In this model, an [IDE Agent](./agents.md#in-ide-agents) could interact with a

remote Coder workspace, or Coder can be used in a remote pipeline or a larger

workflow.

The Coder CLI has options to automatically configure MCP servers for you. On

your local machine, run the following command:

coder mcp claude-desktop # Configure Claude Desktop to interact with Coder

coder mcp cursor # Configure Cursor to interact with Coder

Workspaces can be created, started, and stopped via the Coder CLI. See the

[CLI docs](../../reference/cli/) for more information.

The Coder REST API can be used to manage workspaces and agents. See the

[API docs](../../reference/api/) for more information.

- [Securing Agents](./securing.md)

- A Coder deployment with v2.21 or later

- A [template configured for AI agents](./create-template.md)

- VS Code, Windsurf, or Cursor IDE with the

[Coder Extension](https://github.com/coder/vscode-coder/releases) v1.6.0+ or

the [experimental AI VSIX](https://github.com/coder/vscode-coder/releases/)

Once you have an agent running and reporting activity to Coder, you can view the

status and switch between workspaces from the IDE. This can be very helpful for

reviewing code, working along with the agent, and more.


- [Programmatically manage agents](./headless.md)

- [Securing Agents with Boundaries](./securing.md)