cagent

_vale/config/vocabularies/Docker/accept.txt

@@ -1,6 +1,5 @@
 (?i)[A-Z]{2,}'?s
 
-[Dd]ev
 Adreno
 Aleksandrov
 Amazon
@@ -17,6 +16,7 @@ Bugsnag
 BuildKit
 buildkitd
 BusyBox
+cagent
 CD
 CentOS
 Ceph
@@ -64,6 +64,7 @@ dockerignore
 Dockerize
 Dockerized
 Dockerizing
+Duckduckgo
 Entra
 EPERM
 ESXi
@@ -129,11 +130,11 @@ MySQL
 nameserver
 namespaced?
 namespacing
+Neovim
 netfilter
 netlabel
 netlink
 Netplan
-Neovim
 NFSv\d
 Nginx
 npm
@@ -218,6 +219,7 @@ Zsh
 [Aa]nonymized?
 [Aa]utobuild
 [Aa]llowlist
+[Aa]gentic
 [Aa]utobuilds?
 [Aa]utotests?
 [Bb]uildx
@@ -265,6 +267,7 @@ Zsh
 [Ss]yscalls?
 [Ss]ysfs
 [Tt]eardown
+[Tt]odo
 [Tt]oolchains?
 [Uu]narchived?
 [Uu]ngated

content/manuals/_index.md

@@ -36,7 +36,10 @@ params:
     description: Manage and secure your AI tools with a single gateway.
     icon: /icons/toolkit.svg
     link: /ai/mcp-gateway/
-
+  - title: Cagent
+    description: The open-source multi-agent solution to assist you in your tasks.
+    icon: /icons/cagent.svg
+    link: /ai/cagent
   ai:
   - title: Ask Gordon
     description: Streamline your workflow and get the most out of the Docker ecosystem with your personal AI assistant.

content/manuals/ai/cagent/_index.md

@@ -0,0 +1,260 @@
+---
+title: cagent
+description: cagent lets you build, orchestrate, and share AI agents that work together as a team.
+weight: 60
+params:
+  sidebar:
+    group: Open source
+keywords: [ai, agent, cagent]
+---
+
+{{< summary-bar feature_name="cagent" >}}
+
+[cagent](https://github.com/docker/cagent) lets you build, orchestrate, and share
+AI agents. You can use it to define AI agents that work as a team.
+
+cagent relies on the concept of a _root agent_ that acts as a team lead and
+delegates tasks to the sub-agents you define.
+Each agent:
+- uses the model of your choice, with the parameters of your choice.
+- has access to the [built-in tools](#built-in-tools) and MCP servers
+  configured in the [Docker MCP gateway](/manuals/ai/mcp-gateway/_index.md).
+- works in its own context. They do not share knowledge.
+
+The root agent is your main contact point. Each agent has its own context,
+they don't share knowledge.
+
+## Key features
+
+- ️Multi-tenant architecture with client isolation and session management.
+- Rich tool ecosystem via Model Context Protocol (MCP) integration.
+- Hierarchical agent system with intelligent task delegation.
+- Multiple interfaces including CLI, TUI, API server, and MCP server.
+- Agent distribution via Docker registry integration.
+- Security-first design with proper client scoping and resource isolation.
+- Event-driven streaming for real-time interactions.
+- Multi-model support (OpenAI, Anthropic, Gemini, DMR, Docker AI Gateway).
+
+## Get started with cagent
+
+1. Download the [latest release](https://github.com/docker/cagent/releases)
+   for your operating system.
+
+   > [!NOTE]
+   > You might need to give the binary executable permissions.
+   > On macOS and Linux, run:
+
+     ```console
+     chmod +x /path/to/downloads/cagent-linux-<arm/amd>64
+     ```
+
+   > [!NOTE]
+   > You can also build cagent from the source. See the [repository](https://github.com/docker/cagent?tab=readme-ov-file#build-from-source).
+
+1. Optional: Rename the binary as needed and update your PATH to include
+   cagent's executable.
+
+1. Set the following environment variables:
+
+   ```bash
+   # If using the Docker AI Gateway, set this environment variable or use
+   # the `--models-gateway <url_to_docker_ai_gateway>` CLI flag
+
+   export CAGENT_MODELS_GATEWAY=<url_to_docker_ai_gateway>
+
+   # Alternatively, set keys for remote inference services.
+   # These are not needed if you are using Docker AI Gateway.
+
+   export OPENAI_API_KEY=<your_api_key_here>    # For OpenAI models
+   export ANTHROPIC_API_KEY=<your_api_key_here> # For Anthropic models
+   export GOOGLE_API_KEY=<your_api_key_here>    # For Gemini models
+   ```
+
+1. Create an agent by saving this sample as `assistant.yaml`:
+
+   ```yaml {title="assistant.yaml"}
+   agents:
+     root:
+       model: openai/gpt-5-mini
+       description: A helpful AI assistant
+       instruction: |
+         You are a knowledgeable assistant that helps users with various tasks.
+         Be helpful, accurate, and concise in your responses.
+   ```
+
+1. Start your prompt with your agent:
+
+   ```bash
+   cagent run assistant.yaml
+   ```
+
+## Create an agentic team
+
+You can use AI prompting to generate a team of agents with the `cagent new`
+command:
+
+```console
+$ cagent new
+
+For any feedback, visit: https://docker.qualtrics.com/jfe/form/SV_cNsCIg92nQemlfw
+
+Welcome to cagent! (Ctrl+C to exit)
+
+What should your agent/agent team do? (describe its purpose):
+
+> I need a cross-functional feature team. The team owns a specific product
+  feature end-to-end. Include the key responsibilities of each of the roles
+  involved (engineers, designer, product manager, QA). Keep the description
+  short, clear, and focused on how this team delivers value to users and the business.
+```
+
+Alternatively, you can write your configuration file manually. For example:
+
+```yaml {title="agentic-team.yaml"}
+agents:
+  root:
+    model: claude
+    description: "Main coordinator agent that delegates tasks and manages workflow"
+    instruction: |
+      You are the root coordinator agent. Your job is to:
+      1. Understand user requests and break them down into manageable tasks.
+      2. Delegate appropriate tasks to your helper agent.
+      3. Coordinate responses and ensure tasks are completed properly.
+      4. Provide final responses to the user.
+      When you receive a request, analyze what needs to be done and decide whether to:
+      - Handle it yourself if it's simple.
+      - Delegate to the helper agent if it requires specific assistance.
+      - Break complex requests into multiple sub-tasks.
+    sub_agents: ["helper"]
+
+  helper:
+    model: claude
+    description: "Assistant agent that helps with various tasks as directed by the root agent"
+    instruction: |
+      You are a helpful assistant agent. Your role is to:
+      1. Complete specific tasks assigned by the root agent.
+      2. Provide detailed and accurate responses.
+      3. Ask for clarification if tasks are unclear.
+      4. Report back to the root agent with your results.
+
+      Focus on being thorough and helpful in whatever task you're given.
+
+models:
+  claude:
+    provider: anthropic
+    model: claude-sonnet-4-0
+    max_tokens: 64000
+```
+
+[See the reference documentation](https://github.com/docker/cagent?tab=readme-ov-file#-configuration-reference).
+
+## Built-in tools
+
+cagent includes a set of built-in tools that enhance your agents' capabilities.
+You don't need to configure any external MCP tools to use them.
+
+```yaml
+agents:
+  root:
+    # ... other config
+    toolsets:
+      - type: todo
+      - type: transfer_task
+```
+
+### Think tool
+
+The think tool allows agents to reason through problems step by step:
+
+```yaml
+agents:
+  root:
+    # ... other config
+    toolsets:
+      - type: think
+```
+
+### Todo tool
+
+The todo tool helps agents manage task lists:
+
+```yaml
+agents:
+  root:
+    # ... other config
+    toolsets:
+      - type: todo
+```
+
+### Memory tool
+
+The memory tool provides persistent storage:
+
+```yaml
+agents:
+  root:
+    # ... other config
+    toolsets:
+      - type: memory
+        path: "./agent_memory.db"
+```
+
+### Task transfer tool
+
+The task transfer tool is an internal tool that allows an agent to delegate a task
+to sub-agents. To prevent an agent from delegating work, make sure it doesn't have
+sub-agents defined in its configuration.
+
+### Using tools via the Docker MCP Gateway
+
+If you use the [Docker MCP gateway](/manuals/ai/mcp-gateway.md),
+you can configure your agent to interact with the
+gateway and use the MCP servers configured in it. See [docker mcp
+gateway run](/reference/cli/docker/mcp/gateway/gateway_run.md).
+
+For example, to enable an agent to use Duckduckgo via the MCP Gateway:
+
+```yaml
+toolsets:
+  - type: mcp
+    command: docker
+    args: ["mcp", "gateway", "run", "--servers=duckduckgo"]
+```
+
+## CLI interactive commands
+
+You can use the following CLI commands, during
+CLI sessions with your agents:
+
+| Command  | Description                              |
+|----------|------------------------------------------|
+| /exit    | Exit the program                         |
+| /reset   | Clear conversation history               |
+| /eval    | Save current conversation for evaluation |
+| /compact | Compact the current session              |
+
+## Share your agents
+
+Agent configurations can be packaged and shared via Docker Hub.
+Before you start, make sure you have a [Docker repository](/manuals/docker-hub/repos/create.md).
+
+To push an agent:
+
+```bash
+cagent push ./<agent-file>.yaml <namespace>/<reponame>
+```
+
+To pull an agent to the current directory:
+
+```bash
+cagent pull <namespace>/<reponame>
+```
+
+The agent's configuration file is named `<namespace>_<reponame>.yaml`. Run
+it with the `cagent run <filename>` command.
+
+## Related pages
+
+- For more information about cagent, see the
+[GitHub repository](https://github.com/docker/cagent).
+- [Docker MCP Gateway](/manuals/ai/mcp-gateway/_index.md)