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AWS CodePipeline MCP Server

@cuongdev

This is a Model Context Protocol (MCP) server that integrates with AWS CodePipeline, allowing you to manage your pipelines through Windsurf and Cascade. The server provides a standardized interface for interacting with AWS CodePipeline services.
Overview

What is AWS CodePipeline MCP Server?

AWS CodePipeline MCP Server is a Model Context Protocol (MCP) server that integrates with AWS CodePipeline, enabling users to manage their pipelines through Windsurf and Cascade. It provides a standardized interface for interacting with AWS CodePipeline services.

How to use AWS CodePipeline MCP Server?

To use the server, clone the repository, install dependencies, configure your AWS credentials in a .env file, and start the server. You can then interact with AWS CodePipeline using natural language requests through Windsurf.

Key features of AWS CodePipeline MCP Server?

  • List all pipelines
  • Get pipeline state and detailed definitions
  • List pipeline executions
  • Approve or reject manual approval actions
  • Retry failed stages
  • Trigger pipeline executions
  • View execution logs
  • Stop pipeline executions
  • Tag pipeline resources
  • Create webhooks for automatic triggering
  • Get performance metrics

Use cases of AWS CodePipeline MCP Server?

  1. Managing CI/CD pipelines in AWS CodePipeline.
  2. Automating pipeline executions based on events.
  3. Monitoring pipeline performance and execution states.
  4. Integrating with other tools like GitHub for seamless deployments.

FAQ from AWS CodePipeline MCP Server?

  • What are the prerequisites for using the server?
    You need Node.js (v14 or later), an AWS account with CodePipeline access, and AWS credentials with necessary permissions.

  • Is there a way to troubleshoot common issues?
    Yes! Common issues include connection errors, AWS credential errors, and configuration issues in Windsurf. Check the logs for more details.

  • Can I integrate this server with other tools?
    Yes! The server can be integrated with tools like GitHub for automated pipeline triggering.

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