AWS Pricing MCP
A Model Context Protocol (MCP) server that provides AWS EC2 instance pricing data. This project includes both a traditional server implementation and a serverless Lambda function.
Quick Start
Lambda Deployment (Recommended)
The Lambda function provides the same functionality as the server but with serverless benefits:
# Build and deploy
sam build
sam deploy --guided
# Get the Function URL
aws cloudformation describe-stacks \\
--stack-name aws-pricing-mcp \\
--query 'Stacks[0].Outputs[?OutputKey==`FunctionUrl`].OutputValue' \\
--output text
For detailed Lambda documentation, see LAMBDA.md.
Server Deployment
# Install dependencies
pip install -r requirements.txt
# Run the server
python src/server.py
Features
- EC2 Pricing Data: Find the cheapest EC2 instances based on specifications
- Multiple Pricing Models: On Demand, Reserved Instances, CloudFix RightSpend
- Flexible Filtering: Region, platform, tenancy, vCPU, RAM, GPU, etc.
- JSON-RPC 2.0: Full MCP protocol compliance
- Serverless Option: Lambda function with Function URL
- Dynamic Data: Always up-to-date pricing from S3
Documentation
- LAMBDA.md - Comprehensive Lambda documentation
- MCP.md - MCP protocol examples
- PRICING.md - Pricing data format and sources
- BUILD.md - Build instructions
License
Recommend MCP Servers 💡
mcp-server-kintone
An MCP server that enables AI tools like Claude Desktop to interact with and manipulate kintone data.
@strowk/mcp-k8s
MCP server connecting to Kubernetes
steadybit
MCP Server for Steadybit, enabling LLM tools like Claude to interact with the Steadybit platform.
ms-fabric-mcp
Python-based MCP server for interacting with Microsoft Fabric APIs, with advanced PySpark notebook development, testing, and optimization capabilities with LLM integration.
google_workspace_mcp
Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms, Tasks & Drive with AI - Comprehensive Google Workspace MCP Server
@johnneerdael/netskope-mcp
A Model Context Protocol (MCP) server for managing Netskope Network Private Access (NPA) infrastructure through Large Language Models (LLMs).