AWS App Runner MCP Server
AWS App Runner is a fully managed container application service provided by Amazon Web Services that streamlines the deployment of containerized web applications and APIs at scale.
Quick Start Summary
The AWS App Runner MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS App Runner API through natural language. It exposes 10 API endpoints as callable tools, such as AssociateCustomDomain, CreateAutoScalingConfiguration, CreateConnection, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/amazonaws-com-apprunner. This integration is sourced from the auto AWS App Runner OpenAPI specification (v2020-05-15) and has a quality score of 46/99 (fair documentation coverage).
Server Details
- Category
- Cloud Infrastructure
- Authentication
- None
- Endpoints
- 10 operations
- Transport
- STDIO
- Spec Version
- v2020-05-15
- Install Command
npx -y @mcp/amazonaws-com-apprunner
Environment Variables
AWS_APP_RUNNER_API_KEYExample: your_aws_app_runner_api_key
Top Endpoints
/#X-Amz-Target=AppRunner.AssociateCustomDomainAssociateCustomDomain
/#X-Amz-Target=AppRunner.CreateAutoScalingConfigurationCreateAutoScalingConfiguration
/#X-Amz-Target=AppRunner.CreateConnectionCreateConnection
/#X-Amz-Target=AppRunner.CreateObservabilityConfigurationCreateObservabilityConfiguration
/#X-Amz-Target=AppRunner.CreateServiceCreateService
One-Click Install
Copy the snippet for your MCP client and paste it in — zero editing required.
Claude Desktop
Add to claude_desktop_config.json
{
"mcpServers": {
"amazonaws-com-apprunner": {
"command": "npx",
"args": [
"-y",
"@mcp/amazonaws-com-apprunner"
],
"env": {
"AWS_APP_RUNNER_API_KEY": "your_aws_app_runner_api_key"
}
}
}
}Cursor
Settings → MCP Servers → Add
{
"mcpServers": {
"amazonaws-com-apprunner": {
"url": "https://mcpbridge.org/config/amazonaws-com-apprunner.json"
}
}
}Saves as .cursor/mcp.json in the download. Move it to your project root.
VS Code
Use with MCP extension
{
"mcpServers": {
"amazonaws-com-apprunner": {
"url": "https://mcpbridge.org/config/amazonaws-com-apprunner.json"
}
}
}Endpoints Explorer
Search and browse the 10 operations supported by this server.
Multi-Language Code Examples
Executable code snippets for calling AWS App Runner endpoints in curl, TypeScript, or Python.
curl -X POST "https://api.apis.guru/v2/specs/amazonaws.com/apprunner/2020-05-15/#X-Amz-Target=AppRunner.AssociateCustomDomain" \ -H "Content-Type: application/json" \ # No auth required
Manual Configuration
Directly add this block to your JSON config file, or use the hosted config registry URL.
{
"mcpServers": {
"amazonaws-com-apprunner": {
"command": "npx",
"args": ["-y","@mcp/amazonaws-com-apprunner"],
"env": {
"AWS_APP_RUNNER_API_KEY": "your_aws_app_runner_api_key"
}
}
}
}Authentication Details
No authentication required. This MCP server runs out-of-the-box.
Documentation Links
Error Handling & HTTP Status Code Matrix
Common status codes, error causes, and resolution steps when invoking AWS App Runner endpoints.
400 Bad RequestCause: Malformed payload parameters or missing required fields.
Resolution: Verify request schema in Endpoints tab before calling tool.
401 UnauthorizedCause: Missing or invalid API key credentials.
Resolution: Set environment variable in MCP client config under env object.
403 ForbiddenCause: Insufficient scope permissions for requested resource.
Resolution: Verify key permissions in developer dashboard.
404 Not FoundCause: Resource URL path or requested entity ID does not exist.
Resolution: Check path variables and parameters.
429 Rate Limit ExceededCause: API rate limit quota exceeded.
Resolution: Implement exponential backoff retry in tool call.
500 Internal ErrorCause: Upstream server runtime fault.
Resolution: Inspect STDIO stderr output for log trace.
Quality Score
Checked against our protocol-compliance rules.
Specification Version: v2020-05-15
Page compiled on: June 13, 2026
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📖 Detailed MCP Integration Guide
A technical breakdown of capabilities, agent workflows, and security/configuration best practices.
CreateService, CreateAutoScalingConfiguration, CreateObservabilityConfiguration, and AssociateCustomDomain, allow the AI to execute precise, context-aware actions. For instance, an AI assistant could interpret a natural language command like "Deploy my 'auth-service' from our GitHub main branch and configure it to scale between 2 and 8 instances," and translate it into the correct sequence of API calls—creating a service, defining and applying an auto-scaling configuration, and monitoring the deployment status. This transforms the AI from a code-completion tool into a proactive infrastructure collaborator capable of managing cloud resources with intent.apprunner:CreateService, apprunner:DeleteConnection) and restrict resource access with condition keys where possible. For AI agents operating via MCP, the underlying environment must have AWS credentials (via environment variables, instance profiles, or configured CLI profiles) securely managed. The server setup should never hardcode access keys, and network policies should ensure API calls are made from trusted environments to the AWS API endpoints. Monitoring and auditing all API calls via AWS CloudTrail is essential for maintaining security and compliance in production scenarios.Similar APIs
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