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More renaming in docker agent manuals
Signed-off-by: Guillaume Tardif <guillaume.tardif@gmail.com>
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content/manuals/ai/docker-agent/integrations/_index.md

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@@ -5,7 +5,7 @@ keywords: [docker agent, integration, acp, mcp, a2a, editor, protocol]
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weight: 60
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---
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cagent agents can integrate with different environments depending on how you
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Agents created with Docker Agent can integrate with different environments depending on how you
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want to use them. Each integration type serves a specific purpose.
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## Integration types

content/manuals/ai/docker-agent/integrations/a2a.md

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@@ -18,7 +18,7 @@ tools in MCP clients, see [MCP integration](./mcp.md).
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Before starting an A2A server, you need:
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- cagent installed - See the [installation guide](../_index.md#installation)
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- Docker Agent installed - See the [installation guide](../_index.md#installation)
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- Agent configuration - A YAML file defining your agent. See the
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[tutorial](../tutorial.md)
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- API keys configured - If using cloud model providers (see [Model
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"id": "agent_root",
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"name": "root",
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"description": "A helpful coding assistant",
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"tags": ["llm", "cagent"]
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"tags": ["llm", "dockeragent"]
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}
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],
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"preferredTransport": "jsonrpc",
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## Calling other A2A agents
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Your cagent agents can call remote A2A agents as tools. Configure the A2A
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Your agents can call remote A2A agents as tools. Configure the A2A
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toolset with the remote agent's URL:
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```yaml

content/manuals/ai/docker-agent/integrations/acp.md

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Run agents directly in your editor using the Agent Client Protocol (ACP).
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Your agent gets access to your editor's filesystem context and can read and
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modify files as you work. The editor handles file operations while cagent
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modify files as you work. The editor handles file operations while Docker Agent
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provides the AI capabilities.
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This guide shows you how to configure Neovim, or Zed to run cagent agents. If
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you're looking to expose cagent agents as tools to MCP clients like Claude
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This guide shows you how to configure Neovim, or Zed to run agents with Docker Agent. If
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you're looking to expose agents as tools to MCP clients like Claude
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Desktop or Claude Code, see [MCP integration](./mcp.md) instead.
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## How it works
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When you run cagent with ACP, it becomes part of your editor's environment. You
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When you run Docker Agent with ACP, it becomes part of your editor's environment. You
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select code, highlight a function, or reference a file - the agent sees what you
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see. No copying file paths or switching to a terminal.
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Zed has built-in ACP support.
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1. Add cagent to your agent servers in `settings.json`:
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1. Add `docker agent` to your agent servers in `settings.json`:
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```json
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{
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"agent_servers": {
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"my-cagent-team": {
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"command": "cagent",
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"args": ["acp", "agent.yml"]
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"my-agent-team": {
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"command": "docker",
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"args": ["agent", "serve", "acp", "agent.yml"]
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}
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}
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}
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```
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Replace:
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- `my-cagent-team` with the name you want to use for the agent
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- `my-agent-team` with the name you want to use for the agent
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- `agent.yml` with the path to your agent configuration file.
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If you have multiple agent files that you like to run separately, you can
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1. [Install CodeCompanion](https://codecompanion.olimorris.dev/installation)
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through your plugin manager.
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2. Extend the `cagent` adapter in your CodeCompanion config:
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2. Extend the `dockeragent` adapter in your CodeCompanion config:
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```lua
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require("codecompanion").setup({
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adapters = {
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acp = {
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cagent = function()
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return require("codecompanion.adapters").extend("cagent", {
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dockeragent = function()
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return require("codecompanion.adapters").extend("dockeragent", {
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commands = {
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default = {
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"cagent",
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"docker",
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"agent",
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"serve",
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"acp",
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"agent.yml",
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},
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:CodeCompanion
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```
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4. Switch to the cagent adapter (keymap `ga` in the CodeCompanion buffer, by
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4. Switch to the Docker Agent adapter (keymap `ga` in the CodeCompanion buffer, by
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default).
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See the [CodeCompanion ACP
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{
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"agent_servers": {
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"myagent": {
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"command": "cagent",
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"args": ["acp", "agentcatalog/pirate"]
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"command": "docker",
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"args": ["agent", "serve", "acp", "agentcatalog/pirate"]
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}
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}
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}
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Verify your configuration works:
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1. Start the cagent ACP server using your editor's configured method
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1. Start the Docker Agent ACP server using your editor's configured method
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2. Send a test prompt through your editor's interface
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3. Check that the agent responds
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4. Verify filesystem operations work by asking the agent to read a file

content/manuals/ai/docker-agent/integrations/mcp.md

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weight: 50
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---
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When you run cagent in MCP mode, your agents show up as tools in Claude Desktop
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When you run Docker Agent in MCP mode, your agents show up as tools in Claude Desktop
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and other MCP clients. Instead of switching to a terminal to run your security
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agent, you ask Claude to use it and Claude calls it for you.
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## How it works
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You configure Claude Desktop (or another MCP client) to connect to cagent. Your
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You configure Claude Desktop (or another MCP client) to connect to Docker Agent. Your
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agents appear in Claude's tool list. When you ask Claude to use one, it calls
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that agent through the MCP protocol.
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## MCP Gateway
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Docker provides an [MCP Gateway](/ai/mcp-catalog-and-toolkit/mcp-gateway/) that
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gives cagent agents access to a catalog of pre-configured MCP servers. Instead
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gives agents access to a catalog of pre-configured MCP servers. Instead
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of configuring individual MCP servers, agents can use the gateway to access
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tools like web search, database queries, and more.
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ref: docker:duckduckgo # Uses Docker MCP Gateway
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```
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The `docker:` prefix tells cagent to use the MCP Gateway for this server. See
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The `docker:` prefix tells Docker Agent to use the MCP Gateway for this server. See
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the [MCP Gateway documentation](/ai/mcp-catalog-and-toolkit/mcp-gateway/) for
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available servers and configuration options.
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## MCP client configuration
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Your MCP client needs to know how to start Docker Agent and communicate with it. This
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typically involves adding cagent as an MCP server in your client's
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typically involves adding Docker Agent as an MCP server in your client's
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configuration.
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### Claude Desktop
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Add cagent to your Claude Desktop MCP settings file:
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Add Docker Agent to your Claude Desktop MCP settings file:
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- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
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- Windows: `%APPDATA%\Claude\claude_desktop_config.json`
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- `command`: Full path to your `docker` binary (use `which docker` to find it), or path to `docker-agent` if not using the Docker CLI plugin
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- `args`: MCP command arguments:
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- `mcp`: The subcommand to run cagent in MCP mode
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- `mcp`: The subcommand to run `docker agent` in MCP mode
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- `dockereng/myagent`: Your agent configuration (local file path or OCI
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reference)
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- `--working-dir`: Optional working directory for agent execution
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### Claude Code
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Add cagent as an MCP server using the `claude mcp add` command:
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Add Docker Agent as an MCP server using the `claude mcp add` command:
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```console
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$ claude mcp add --transport stdio myagent \
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--env OPENAI_API_KEY=$OPENAI_API_KEY \
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--env ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
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-- cagent mcp /path/to/agent.yml --working-dir $(pwd)
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-- docker agent serve mcp /path/to/agent.yml --working-dir $(pwd)
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```
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Command breakdown:
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- `myagent`: Name for this MCP server in Claude Code
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- `--env`: Pass environment variables (repeat for each variable)
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- `--`: Separates Claude Code options from the MCP server command
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- `docker agent serve mcp /path/to/agent.yml`: The cagent MCP command with the path to your
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- `docker agent serve mcp /path/to/agent.yml`: The Docker Agent MCP command with the path to your
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agent configuration
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- `--working-dir $(pwd)`: Set the working directory for agent execution
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For other MCP-compatible clients, you need to:
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1. Start cagent with `docker agent serve mcp /path/to/agent.yml --working-dir /project/path`
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1. Start Docker Agent with `docker agent serve mcp /path/to/agent.yml --working-dir /project/path`
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2. Configure the client to communicate with Docker Agent over stdio
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3. Pass required environment variables (API keys, etc.)
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Verify your MCP integration works:
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1. Restart your MCP client after configuration changes
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2. Check that cagent agents appear as available tools
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2. Check that agents appear as available tools
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3. Invoke an agent with a simple test prompt
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4. Verify the agent can access its configured tools (filesystem, shell, etc.)
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If agents don't appear or fail to execute, check:
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- `cagent` binary path is correct and executable
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- `docker agent` command is available and executable
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- Agent configuration file exists and is valid
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- All required API keys are set in environment variables
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- Working directory path exists and has appropriate permissions

content/manuals/ai/docker-agent/model-providers.md

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---
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To run cagent, you need a model provider. You can either use a cloud provider
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To run Docker Agent, you need a model provider. You can either use a cloud provider
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with an API key or run models locally with [Docker Model
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Runner](local-models.md).
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## Supported providers
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cagent supports these cloud model providers:
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Docker Agent supports these cloud model providers:
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- Anthropic - Claude models
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- OpenAI - GPT models
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base_url: https://your-provider.example.com/v1
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```
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By default, cagent uses the `OPENAI_API_KEY` environment variable for
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By default, Docker Agent uses the `OPENAI_API_KEY` environment variable for
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authentication. If your provider uses a different variable, specify it with
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`token_key`:
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content/manuals/ai/docker-agent/rag.md

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rag: [codebase]
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```
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When you reference `rag: [codebase]`, cagent:
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When you reference `rag: [codebase]`, Docker Agent:
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1. **At startup** - Indexes your documents (first run only, blocks until complete)
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2. **During conversation** - Gives the agent a search tool
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### The indexing process
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On first run, cagent:
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On first run, Docker Agent:
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- Reads files from configured paths
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- Respects `.gitignore` patterns (can be disabled)
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- Splits documents into chunks
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- Creates searchable representations using your chosen strategy
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- Stores everything in a local database
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Subsequent runs reuse the index. If files change, cagent detects this and
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Subsequent runs reuse the index. If files change, Docker Agent detects this and
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re-indexes only what changed, keeping your knowledge base up to date without
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manual intervention.
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## Retrieval strategies
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Different content requires different retrieval approaches. cagent supports
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Different content requires different retrieval approaches. Docker Agent supports
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three strategies, each optimized for different use cases. The defaults work
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well, but understanding the trade-offs helps you choose the right approach.
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content/manuals/ai/docker-agent/reference/config.md

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---
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title: Configuration file reference
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linkTitle: Configuration file
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description: Complete reference for the cagent YAML configuration file format
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description: Complete reference for the Docker Agent YAML configuration file format
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keywords: [ai, agent, cagent, configuration, yaml]
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### Docker Model Runner (DMR)
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Run local models. If `base_url` is omitted, cagent auto-discovers via Docker
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Run local models. If `base_url` is omitted, Docker Agent auto-discovers via Docker
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Model plugin.
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```yaml

content/manuals/ai/docker-agent/reference/examples.md

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Get inspiration from the following agent examples.
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See more examples in the [cagent GitHub repository](https://github.com/docker/cagent/tree/main/examples).
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See more examples in the [Docker Agent GitHub repository](https://github.com/docker/cagent/tree/main/examples).
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## Development team
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content/manuals/ai/docker-agent/reference/toolsets.md

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1. Agent analyzes the task and determines which tool to use
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2. Agent constructs tool parameters based on requirements
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3. cagent executes the tool and returns results
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3. Docker Agent executes the tool and returns results
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4. Agent processes results and decides next steps
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Agents can call multiple tools in sequence or make decisions based on tool
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## Tool types
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cagent supports three types of toolsets:
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Docker Agent supports three types of toolsets:
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Built-in toolsets
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: Core functionality built directly into cagent (`filesystem`, `shell`,
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: Core functionality built directly into Docker Agent (`filesystem`, `shell`,
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`memory`, etc.). These provide essential capabilities for file operations,
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command execution, and state management.
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MCP toolsets
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run commands in the foreground or background.
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Commands execute in the current working directory and inherit environment
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variables from the cagent process. This toolset is powerful but should be used
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variables from the Docker Agent process. This toolset is powerful but should be used
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with appropriate security considerations.
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#### Configuration
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incomplete dependencies. Tasks are sorted by priority and blocking status,
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making it easy to identify the next actionable work.
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Tasks are stored in a JSON file and persist across cagent sessions.
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Tasks are stored in a JSON file and persist across Docker Agent sessions.
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#### Configuration
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for agents that interact with users over time or need to maintain state about
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Memories are stored in a local database file and persist across cagent
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Memories are stored in a local database file and persist across Docker Agent
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sessions.
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#### Configuration

content/manuals/ai/docker-agent/sharing-agents.md

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{
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"agent_servers": {
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"myagent": {
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"command": "cagent",
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"args": ["acp", "agentcatalog/pirate"]
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"command": "docker",
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"args": ["agent", "aserve", "acp", "agentcatalog/pirate"]
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}
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}
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}

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