registry/registry/coder/modules/claude-code

display_name	description	icon	verified	tags
Claude Code	Run the Claude Code agent in your workspace.	../../../../.icons/claude.svg	true	agent claude-code ai tasks anthropic

Claude Code

Run the Claude Code agent in your workspace to generate code and perform tasks. This module integrates with AgentAPI for task reporting in the Coder UI.

module "claude-code" {
  source         = "registry.coder.com/coder/claude-code/coder"
  version        = "4.4.1"
  agent_id       = coder_agent.main.id
  workdir        = "/home/coder/project"
  claude_api_key = "xxxx-xxxxx-xxxx"
}

Warning

Security Notice: This module uses the --dangerously-skip-permissions flag when running Claude Code tasks. This flag bypasses standard permission checks and allows Claude Code broader access to your system than normally permitted. While this enables more functionality, it also means Claude Code can potentially execute commands with the same privileges as the user running it. Use this module only in trusted environments and be aware of the security implications.

Note

By default, this module is configured to run the embedded chat interface as a path-based application. In production, we recommend that you configure a wildcard access URL and set subdomain = true. See here for more details.

Prerequisites

• An Anthropic API key or a Claude Session Token is required for tasks.
  • You can get the API key from the Anthropic Console.
  • You can get the Session Token using the claude setup-token command. This is a long-lived authentication token (requires Claude subscription)

Session Resumption Behavior

By default, Claude Code automatically resumes existing conversations when your workspace restarts. Sessions are tracked per workspace directory, so conversations continue where you left off. If no session exists (first start), your ai_prompt will run normally. To disable this behavior and always start fresh, set continue = false

Examples

Usage with Agent Boundaries

This example shows how to configure the Claude Code module to run the agent behind a process-level boundary that restricts its network access.

module "claude-code" {
  source           = "registry.coder.com/coder/claude-code/coder"
  version          = "4.4.1"
  agent_id         = coder_agent.main.id
  workdir          = "/home/coder/project"
  enable_boundary  = true
  boundary_version = "v0.5.1"
}

Usage with Tasks and Advanced Configuration

This example shows how to configure the Claude Code module with an AI prompt, API key shared by all users of the template, and other custom settings.

Note

When a specific claude_code_version (other than "latest") is provided, the module will install Claude Code via npm instead of the official installer. This allows for version pinning. The claude_binary_path variable can be used to specify where a pre-installed Claude binary is located.

data "coder_parameter" "ai_prompt" {
  type        = "string"
  name        = "AI Prompt"
  default     = ""
  description = "Initial task prompt for Claude Code."
  mutable     = true
}

module "claude-code" {
  source   = "registry.coder.com/coder/claude-code/coder"
  version  = "4.4.1"
  agent_id = coder_agent.main.id
  workdir  = "/home/coder/project"

  claude_api_key = "xxxx-xxxxx-xxxx"
  # OR
  claude_code_oauth_token = "xxxxx-xxxx-xxxx"

  claude_code_version = "2.0.62"          # Pin to a specific version (uses npm)
  claude_binary_path  = "/opt/claude/bin" # Path to pre-installed Claude binary
  agentapi_version    = "0.11.4"

  ai_prompt = data.coder_parameter.ai_prompt.value
  model     = "sonnet"

  permission_mode = "plan"

  mcp = <<-EOF
  {
    "mcpServers": {
      "my-custom-tool": {
        "command": "my-tool-server",
        "args": ["--port", "8080"]
      }
    }
  }
  EOF
}

Standalone Mode

Run and configure Claude Code as a standalone CLI in your workspace.

module "claude-code" {
  source              = "registry.coder.com/coder/claude-code/coder"
  version             = "4.4.1"
  agent_id            = coder_agent.main.id
  workdir             = "/home/coder/project"
  install_claude_code = true
  claude_code_version = "2.0.62"
  report_tasks        = false
}

Usage with Claude Code Subscription

variable "claude_code_oauth_token" {
  type        = string
  description = "Generate one using `claude setup-token` command"
  sensitive   = true
  value       = "xxxx-xxx-xxxx"
}

module "claude-code" {
  source                  = "registry.coder.com/coder/claude-code/coder"
  version                 = "4.4.1"
  agent_id                = coder_agent.main.id
  workdir                 = "/home/coder/project"
  claude_code_oauth_token = var.claude_code_oauth_token
}

Usage with AWS Bedrock

Prerequisites

AWS account with Bedrock access, Claude models enabled in Bedrock console, appropriate IAM permissions.

Configure Claude Code to use AWS Bedrock for accessing Claude models through your AWS infrastructure.

resource "coder_env" "bedrock_use" {
  agent_id = coder_agent.main.id
  name     = "CLAUDE_CODE_USE_BEDROCK"
  value    = "1"
}

resource "coder_env" "aws_region" {
  agent_id = coder_agent.main.id
  name     = "AWS_REGION"
  value    = "us-east-1" # Choose your preferred region
}

# Option 1: Using AWS credentials

variable "aws_access_key_id" {
  type        = string
  description = "Your AWS access key ID. Create this in the AWS IAM console under 'Security credentials'."
  sensitive   = true
  value       = "xxxx-xxx-xxxx"
}

variable "aws_secret_access_key" {
  type        = string
  description = "Your AWS secret access key. This is shown once when you create an access key in the AWS IAM console."
  sensitive   = true
  value       = "xxxx-xxx-xxxx"
}

resource "coder_env" "aws_access_key_id" {
  agent_id = coder_agent.main.id
  name     = "AWS_ACCESS_KEY_ID"
  value    = var.aws_access_key_id
}

resource "coder_env" "aws_secret_access_key" {
  agent_id = coder_agent.main.id
  name     = "AWS_SECRET_ACCESS_KEY"
  value    = var.aws_secret_access_key
}

# Option 2: Using Bedrock API key (simpler)

variable "aws_bearer_token_bedrock" {
  type        = string
  description = "Your AWS Bedrock bearer token. This provides access to Bedrock without needing separate access key and secret key."
  sensitive   = true
  value       = "xxxx-xxx-xxxx"
}

resource "coder_env" "bedrock_api_key" {
  agent_id = coder_agent.main.id
  name     = "AWS_BEARER_TOKEN_BEDROCK"
  value    = var.aws_bearer_token_bedrock
}

module "claude-code" {
  source   = "registry.coder.com/coder/claude-code/coder"
  version  = "4.4.1"
  agent_id = coder_agent.main.id
  workdir  = "/home/coder/project"
  model    = "global.anthropic.claude-sonnet-4-5-20250929-v1:0"
}

Note

For additional Bedrock configuration options (model selection, token limits, region overrides, etc.), see the Claude Code Bedrock documentation.

Usage with Google Vertex AI

Prerequisites

GCP project with Vertex AI API enabled, Claude models enabled through Model Garden, service account with Vertex AI permissions, appropriate IAM permissions (Vertex AI User role).

Configure Claude Code to use Google Vertex AI for accessing Claude models through Google Cloud Platform.

variable "vertex_sa_json" {
  type        = string
  description = "The complete JSON content of your Google Cloud service account key file. Create a service account in the GCP Console under 'IAM & Admin > Service Accounts', then create and download a JSON key. Copy the entire JSON content into this variable."
  sensitive   = true
}

resource "coder_env" "vertex_use" {
  agent_id = coder_agent.main.id
  name     = "CLAUDE_CODE_USE_VERTEX"
  value    = "1"
}

resource "coder_env" "vertex_project_id" {
  agent_id = coder_agent.main.id
  name     = "ANTHROPIC_VERTEX_PROJECT_ID"
  value    = "your-gcp-project-id"
}

resource "coder_env" "cloud_ml_region" {
  agent_id = coder_agent.main.id
  name     = "CLOUD_ML_REGION"
  value    = "global"
}

resource "coder_env" "vertex_sa_json" {
  agent_id = coder_agent.main.id
  name     = "VERTEX_SA_JSON"
  value    = var.vertex_sa_json
}

resource "coder_env" "google_application_credentials" {
  agent_id = coder_agent.main.id
  name     = "GOOGLE_APPLICATION_CREDENTIALS"
  value    = "/tmp/gcp-sa.json"
}

module "claude-code" {
  source   = "registry.coder.com/coder/claude-code/coder"
  version  = "4.4.1"
  agent_id = coder_agent.main.id
  workdir  = "/home/coder/project"
  model    = "claude-sonnet-4@20250514"

  pre_install_script = <<-EOT
    #!/bin/bash
    # Write the service account JSON to a file
    echo "$VERTEX_SA_JSON" > /tmp/gcp-sa.json

    # Install prerequisite packages
    sudo apt-get update
    sudo apt-get install -y apt-transport-https ca-certificates gnupg curl

    # Add Google Cloud public key
    curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo gpg --dearmor -o /usr/share/keyrings/cloud.google.gpg

    # Add Google Cloud SDK repo to apt sources
    echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | sudo tee /etc/apt/sources.list.d/google-cloud-sdk.list

    # Update and install the Google Cloud SDK
    sudo apt-get update && sudo apt-get install -y google-cloud-cli

    # Authenticate gcloud with the service account
    gcloud auth activate-service-account --key-file=/tmp/gcp-sa.json
  EOT
}

Note

For additional Vertex AI configuration options (model selection, token limits, region overrides, etc.), see the Claude Code Vertex AI documentation.

Troubleshooting

If you encounter any issues, check the log files in the ~/.claude-module directory within your workspace for detailed information.

# Installation logs
cat ~/.claude-module/install.log

# Startup logs
cat ~/.claude-module/agentapi-start.log

# Pre/post install script logs
cat ~/.claude-module/pre_install.log
cat ~/.claude-module/post_install.log

Note

To use tasks with Claude Code, you must provide an anthropic_api_key or claude_code_oauth_token. The workdir variable is required and specifies the directory where Claude Code will run.

References

• Claude Code Documentation
• AgentAPI Documentation
• Coder AI Agents Guide