About AWS MCP Server
AWS MCP Server connects Claude Desktop and other MCP clients to AWS services. It combines service-specific operations with a generic AWS SDK wrapper and an optional document search capability.
Key features
- 01Browse S3 buckets and objects
- 02Inspect EC2, RDS, and CloudWatch
- 03Retrieve Cost Explorer reports
- 04Call AWS operations through SDK wrapper
- 05Optional document ingestion and search
Use cases
- 01Review AWS resources from an MCP client
- 02Retrieve metrics and cost usage reports
- 03Run AWS SDK operations through a client
- 04Ingest and search documents with vector store
MCP support
It exposes AWS service operations as tools for MCP clients, including Claude Desktop. An optional vector store supports document ingestion and search.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEAWS MCP Server
A Model Context Protocol (MCP) server that provides tools to interact with AWS services through Claude Desktop.
Features
- S3: List buckets, list objects
- EC2: Describe instances, security groups, VPCs
- RDS: Describe database instances
- Cost Explorer: Get cost and usage reports
- CloudWatch: Retrieve metric statistics
- Generic AWS SDK: Access any AWS operation via
aws_sdk_wrapper - Vector Store: Optional document ingestion and search capabilities
Quick Start
Prerequisites
- Python 3.12+
- AWS credentials configured (
~/.aws/credentials) - Claude Desktop installed
Installation
-
Install the package:
pip install aws-mcp-server -
Configure Claude Desktop: Add to your
claude_desktop_config.json:{ "mcpServers": { "aws-mcp-server": { "command": "aws-mcp-server" } } } -
Configure AWS credentials:
aws configure # OR manually edit ~/.aws/credentials:[default] aws_access_key_id = YOUR_ACCESS_KEY aws_secret_access_key = YOUR_SECRET_KEY region = us-east-1
Development
Local Development Setup
# Clone and install
git clone <repository-url>
cd aws-mcp-server
uv sync
# Run locally
uvx .
Configuration Options
Set environment variables for customization:
export AWS_MCP_PORT=8888
export AWS_MCP_DEBUG=true
export ENABLE_VECTOR_STORE=true
Documentation
- Deployment Guide - Production deployment with AWS App Runner
- Vector Store Guide - Document ingestion and search setup
- Workflow Guide - Development workflows and patterns
License
MIT License - see LICENSE file for details.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.