AWS Resources MCP Server

Overview

A Model Context Protocol (MCP) server implementation that provides running generated python code to query any AWS resources through boto3.

At your own risk: I didn't limit the operations to ReadyOnly, so that cautious Ops people can be helped using this tool doing management operations. Your AWS user role will dictate the permissions for what you can do.

Demo: Fix Dynamodb Permission Error

https://github.com/user-attachments/assets/de88688d-d7a0-45e1-94eb-3f5d71e9a7c7

Why Another AWS MCP Server?

I tried AWS Chatbot with Developer Access. Free Tier has a limit of 25 query/month for resources. Next tier is $19/month include 90% of the features I don't use. And the results are in a fashion of JSON and a lot of restrictions.

I tried using aws-mcp but ran into a few issues:

1. Setup Hassle: Had to clone a git repo and deal with local setup
2. Stability Issues: Wasn't stable enough on my Mac
3. Node.js Stack: As a Python developer, I couldn't effectively contribute back to the Node.js codebase

So I created this new approach that:

• Runs directly from a Docker image - no git clone needed
• Uses Python and boto3 for better stability
• Makes it easy for Python folks to contribute
• Includes proper sandboxing for code execution
• Keeps everything containerized and clean

For more information about the Model Context Protocol and how it works, see Anthropic's MCP documentation.

Components

Resources

The server exposes the following resource:

• aws://query_resources: A dynamic resource that provides access to AWS resources through boto3 queries

Example Queries

Here are some example queries you can execute:

1. List S3 buckets:

s3 = session.client('s3')
result = s3.list_buckets()

2. Get latest CodePipeline deployment:

def get_latest_deployment(pipeline_name):
    codepipeline = session.client('codepipeline')

    result = codepipeline.list_pipeline_executions(
        pipelineName=pipeline_name,
        maxResults=5
    )

    if result['pipelineExecutionSummaries']:
        latest_execution = max(
            [e for e in result['pipelineExecutionSummaries']
             if e['status'] == 'Succeeded'],
            key=itemgetter('startTime'),
            default=None
        )

        if latest_execution:
            result = codepipeline.get_pipeline_execution(
                pipelineName=pipeline_name,
                pipelineExecutionId=latest_execution['pipelineExecutionId']
            )
        else:
            result = None
    else:
        result = None

    return result

result = get_latest_deployment("your-pipeline-name")

Note: All code snippets must set a result variable that will be returned to the client. The result variable will be automatically converted to JSON format, with proper handling of AWS-specific objects and datetime values.

Tools

The server offers a tool for executing AWS queries:

• aws_resources_query_or_modify
  • Execute a boto3 code snippet to query or modify AWS resources
  • Input:
    • code_snippet (string): Python code using boto3 to query AWS resources
    • The code must set a `

... View full README on GitHub