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Cloud InfrastructureQuality Score: 46

AWS App Runner MCP Configuration

The AWS App Runner MCP configuration provides a hosted JSON schema that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS App Runner API via the Model Context Protocol. This configuration maps 10 API endpoints as callable tools, including AssociateCustomDomain, CreateAutoScalingConfiguration, CreateConnection, and more. No authentication credentials are needed — it works out of the box. The configuration is auto-generated from the AWS App Runner OpenAPI specification (v2020-05-15) and has a quality score of 46/99 (fair documentation coverage). Use the hosted URL below to auto-load this schema into any compatible MCP client.

Quick Specs Reference

AuthenticationNo Auth Required
Available Endpoints10 tools mapped
Integration Modeauto Generation

Hosted Config URL

Use this hosted URL in any client that supports remote MCP schema auto-loading.

https://mcpbridge.org/config/amazonaws-com-apprunner.json

One-Click Client Setup

Copy the configurations below to wire your local coding assistant directly.

Claude Desktop

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 & VS Code

MCP Server URL Setup
{
  "mcpServers": {
    "amazonaws-com-apprunner": {
      "url": "https://mcpbridge.org/config/amazonaws-com-apprunner.json"
    }
  }
}

Raw Configuration JSON

For local command line wrappers or dynamic shell bindings.

{
  "mcpServers": {
    "amazonaws-com-apprunner": {
      "command": "npx",
      "args": ["-y","@mcp/amazonaws-com-apprunner"],
      "env": {
      "AWS_APP_RUNNER_API_KEY": "your_aws_app_runner_api_key"
}
    }
  }
}

Required Environment Keys

Substitute these secrets inside your configuration directory environment definitions.

AWS_APP_RUNNER_API_KEY
Replace your_aws_app_runner_api_key with your secret key credential

Mapped Web APIs & Tools

The following routes will be exposed directly as protocol tools for the LLM.

POST/#X-Amz-Target=AppRunner.AssociateCustomDomain

AssociateCustomDomain

POST/#X-Amz-Target=AppRunner.CreateAutoScalingConfiguration

CreateAutoScalingConfiguration

POST/#X-Amz-Target=AppRunner.CreateConnection

CreateConnection

POST/#X-Amz-Target=AppRunner.CreateObservabilityConfiguration

CreateObservabilityConfiguration

POST/#X-Amz-Target=AppRunner.CreateService

CreateService

POST/#X-Amz-Target=AppRunner.CreateVpcConnector

CreateVpcConnector

POST/#X-Amz-Target=AppRunner.CreateVpcIngressConnection

CreateVpcIngressConnection

POST/#X-Amz-Target=AppRunner.DeleteAutoScalingConfiguration

DeleteAutoScalingConfiguration

POST/#X-Amz-Target=AppRunner.DeleteConnection

DeleteConnection

POST/#X-Amz-Target=AppRunner.DeleteObservabilityConfiguration

DeleteObservabilityConfiguration

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DigitalOcean API

The DigitalOcean API is a comprehensive, RESTful interface provided by DigitalOcean, a leading cloud infrastructure provider focused on simplifying cloud computing for developers, startups, and enterprises. It serves as the programmatic backbone for managing the entire DigitalOcean ecosystem, enabling users to provision, configure, and control cloud resources such as Droplets (virtual private servers), Kubernetes clusters, managed databases, networks, storage volumes, and application platforms. Core capabilities include full lifecycle management of these resources, from creation and scaling to monitoring and deletion, mirroring the functionality available in the DigitalOcean control panel. Its primary use cases range from automating infrastructure setup for CI/CD pipelines and enabling infrastructure-as-code practices to supporting dynamic application scaling and resource optimization for SaaS products, e-commerce sites, and development environments. The API is designed for both developers seeking to automate their cloud operations and businesses that require programmable, scalable cloud infrastructure without the complexity of larger hyperscale providers. When exposed as tools via the Model Context Protocol (MCP) to an AI coding assistant, the DigitalOcean API transforms from a traditional developer tool into a dynamic, context-aware resource for intelligent infrastructure automation. The MCP server acts as a bridge, allowing the AI model to understand and execute API calls based on natural language instructions and the current project context. This integration provides immense value by enabling the AI to perform real-time cloud management tasks directly within the development workflow. For instance, the AI can instantly query account details to verify resources, list and manage SSH keys for secure access, or retrieve and monitor the status of infrastructure actions. This contextual access means the AI can make informed suggestions or take automated actions—like recommending a cost-optimized Droplet size based on current usage patterns or verifying that a new SSH key has been correctly added before proceeding with a deployment script—thereby reducing context-switching and accelerating development cycles. Practical workflow examples demonstrate the power of this MCP integration. A developer could instruct the AI agent with commands like, "Query our account for all active SSH keys and ensure the one named 'ci-bot' is present; if not, create it using this public key," automating a common security and setup step. Another example involves asking the AI to "Check the status of our last ten infrastructure actions to see if any are stuck in a 'pending' state," which would leverage the actions endpoints to provide an immediate operational health check. More complex automations are possible, such as "Based on the current Droplet inventory from the API, generate a Terraform configuration file that replicates this setup," or "Scan our Kubernetes 1-Click apps and suggest one for deploying a new microservice based on the project requirements." These interactions turn the AI into a proactive DevOps partner capable of auditing, reporting, and modifying cloud infrastructure through simple, conversational directives. Critical to the secure operation of this MCP server is rigorous attention to authentication and access control, despite any initial configuration notes indicating "None" for simplicity. In any real-world deployment, authentication via a DigitalOcean Personal Access Token is non-negotiable. This token should be treated as a high-privilege secret. Developers must adhere to the principle of least privilege by creating tokens with the minimum scopes required for the specific tasks—such as read-only access for monitoring or write access only for specific resource types. Best practices include storing tokens in secure environment variables or a secrets manager, never hardcoding them, and ensuring the MCP server configuration does not expose them in logs or client-side code. Furthermore, regular token rotation and monitoring of API activity through DigitalOcean's audit logs are essential to maintain a secure posture when integrating cloud management capabilities directly into AI-assisted development environments.

https://mcpbridge.org/config/digitalocean-com.json