Aws Resources Python
    Aws Resources Python

    Aws Resources Python

    A Python-based MCP server that lets Claude run boto3 code to query and manage AWS resources. Execute powerful AWS operations directly through Claude with proper sandboxing and containerization. No need for complex setups - just pass your AWS credentials and start interacting with all AWS services.

    3.3

    GitHub Stats

    Stars

    17

    Forks

    10

    Release Date

    4/22/2025

    about 2 months ago

    Detailed Description

    AWS Resources MCP Server

    Docker Hub Docker Hub

    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()
    
    1. 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 result variable with the query output
      • Allowed imports:
        • boto3
        • operator
        • json
        • datetime
        • pytz
        • dateutil
        • re
        • time
      • Available built-in functions:
        • Basic types: dict, list, tuple, set, str, int, float, bool
        • Operations: len, max, min, sorted, filter, map, sum, any, all
        • Object handling: hasattr, getattr, isinstance
        • Other: print, import

    Implementation Details

    The server includes several safety features:

    • AST-based code analysis to validate imports and code structure
    • Restricted execution environment with limited built-in functions
    • JSON serialization of results with proper handling of AWS-specific objects
    • Proper error handling and reporting

    Setup

    Prerequisites

    You'll need AWS credentials with appropriate permissions to query AWS resources. You can obtain these by:

    1. Creating an IAM user in your AWS account
    2. Generating access keys for programmatic access
    3. Ensuring the IAM user has necessary permissions for the AWS services you want to query

    The following environment variables are required:

    • AWS_ACCESS_KEY_ID: Your AWS access key
    • AWS_SECRET_ACCESS_KEY: Your AWS secret key
    • AWS_SESSION_TOKEN: (Optional) AWS session token if using temporary credentials
    • AWS_DEFAULT_REGION: AWS region (defaults to 'us-east-1' if not set)

    You can also use a profile stored in the ~/.aws/credentials file. To do this, set the AWS_PROFILE environment variable to the profile name.

    Note: Keep your AWS credentials secure and never commit them to version control.

    Installing via Smithery

    To install AWS Resources MCP Server for Claude Desktop automatically via Smithery:

    npx -y @smithery/cli install mcp-server-aws-resources-python --client claude
    

    Docker Installation

    You can either build the image locally or pull it from Docker Hub. The image is built for the Linux platform.

    Supported Platforms

    • Linux/amd64
    • Linux/arm64
    • Linux/arm/v7

    Option 1: Pull from Docker Hub

    docker pull buryhuang/mcp-server-aws-resources:latest
    

    Option 2: Build Locally

    docker build -t mcp-server-aws-resources .
    

    Run the container:

    docker run \
      -e AWS_ACCESS_KEY_ID=your_access_key_id_here \
      -e AWS_SECRET_ACCESS_KEY=your_secret_access_key_here \
      -e AWS_DEFAULT_REGION=your_AWS_DEFAULT_REGION \
      buryhuang/mcp-server-aws-resources:latest
    

    Or using stored credentials and a profile:

    docker run \
      -e AWS_PROFILE=[AWS_PROFILE_NAME] \
      -v ~/.aws:/root/.aws \
      buryhuang/mcp-server-aws-resources:latest
    

    Cross-Platform Publishing

    To publish the Docker image for multiple platforms, you can use the docker buildx command. Follow these steps:

    1. Create a new builder instance (if you haven't already):

      docker buildx create --use
      
    2. Build and push the image for multiple platforms:

      docker buildx build --platform linux/amd64,linux/arm64,linux/arm/v7 -t buryhuang/mcp-server-aws-resources:latest --push .
      
    3. Verify the image is available for the specified platforms:

      docker buildx imagetools inspect buryhuang/mcp-server-aws-resources:latest
      

    Usage with Claude Desktop

    Running with Docker

    Example using ACCESS_KEY_ID and SECRET_ACCESS_KEY

    {
      "mcpServers": {
        "aws-resources": {
          "command": "docker",
          "args": [
            "run",
            "-i",
            "--rm",
            "-e",
            "AWS_ACCESS_KEY_ID=your_access_key_id_here",
            "-e",
            "AWS_SECRET_ACCESS_KEY=your_secret_access_key_here",
            "-e",
            "AWS_DEFAULT_REGION=us-east-1",
            "buryhuang/mcp-server-aws-resources:latest"
          ]
        }
      }
    }
    

    Example using PROFILE and mounting local AWS credentials

    {
      "mcpServers": {
        "aws-resources": {
          "command": "docker",
          "args": [
            "run",
            "-i",
            "--rm",
            "-e",
            "AWS_PROFILE=default",
            "-v",
            "~/.aws:/root/.aws",
            "buryhuang/mcp-server-aws-resources:latest"
          ]
        }
      }
    }
    

    Running with Git clone

    Example running with git clone and profile

    {
      "mcpServers": {
        "aws": {
          "command": "/Users/gmr/.local/bin/uv",
          "args": [
            "--directory",
            "/<your-path>/mcp-server-aws-resources-python",
            "run",
            "src/mcp_server_aws_resources/server.py",
            "--profile",
            "testing"
          ]
        }
      }
    }
    

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