Built using Python and provides AWS service recommendations through Python-based tools for suggesting appropriate AWS services based on use case descriptions and browsing AWS services by category.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AWS Advisor MCP Serversuggest AWS services for a scalable web application"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AWS Advisor MCP Server
A Model Context Protocol (MCP) server that provides AWS service recommendations based on your use case descriptions.
Features
suggest_aws_service: Get AWS service recommendations by describing your use case
list_aws_categories: Browse AWS services organized by category (compute, storage, database, etc.)
Setup
Install uv (if not already installed):
curl -LsSf https://astral.sh/uv/install.sh | shSync dependencies:
uv syncThis will create a virtual environment and install all dependencies.
Configuration for Cursor IDE
Add this server to your Cursor MCP settings:
Open Cursor Settings
Navigate to the MCP section
Add a new server with this configuration:
{
"mcpServers": {
"aws-advisor": {
"command": "uv",
"args": [
"--directory",
"/Users/antonioschaffert/workspace/tony/my-dev-mcp",
"run",
"python",
"src/aws_advisor_server.py"
]
}
}
}Or add it to your MCP config file (usually ~/.cursor/mcp_config.json or similar):
{
"aws-advisor": {
"command": "uv",
"args": [
"--directory",
"/Users/antonioschaffert/workspace/tony/my-dev-mcp",
"run",
"python",
"src/aws_advisor_server.py"
]
}
}Usage
Once configured, you can use the tools in Cursor:
Example prompts:
"What AWS service should I use for serverless computing?"
"Suggest AWS services for storing images"
"What's the best AWS service for a relational database?"
"Show me AWS services for real-time data streaming"
"List all AWS categories"
Available Tools:
suggest_aws_service
Input:
use_case(string) - Description of what you want to buildReturns: Recommended AWS services with explanations
list_aws_categories
No input required
Returns: All AWS service categories and their services
Testing Locally
You can test the server directly:
uv run python src/aws_advisor_server.pyThen send MCP protocol messages via stdin (for advanced testing).
Covered AWS Services
Compute: EC2, Lambda, ECS, EKS, Fargate, Lightsail
Storage: S3, EBS, EFS, Glacier, FSx
Database: RDS, DynamoDB, Aurora, DocumentDB, ElastiCache, Neptune, Redshift
Networking: VPC, CloudFront, Route53, API Gateway, Direct Connect, ELB
Analytics: Athena, EMR, Kinesis, Glue, QuickSight
ML/AI: SageMaker, Rekognition, Comprehend, Polly, Transcribe, Translate, Lex
Security: IAM, Cognito, KMS, Secrets Manager, WAF, GuardDuty
Messaging: SQS, SNS, EventBridge, SES
Monitoring: CloudWatch, X-Ray, CloudTrail
Requirements
Python 3.10+
mcp package (>=0.9.0)