Log Analyzer With CloudWatch Logs

🚀 Log Analyzer Based on MCP

A Model Context Protocol (MCP) server that enables AI assistants to access and analyze, search, and correlate logs from AWS CloudWatch Logs.

🏗️ Architecture

🔌 Model Context Protocol (MCP)

As described by Anthropic:

MCP is an open protocol that standardizes the way applications provide context to large language models (LLMs). Think of MCP as the USB-C port for AI applications. Just as USB-C provides a universal way for your devices to connect to various peripherals and accessories, MCP provides a universal way for AI models to connect to different data sources and tools.

This repository contains an example client and server that allow an AI assistant like Claude to interact with CloudWatch logs in an AWS account. For more information, read the Introduction.

✨ Features

• Detect and search CloudWatch log groups
• Search logs using CloudWatch Logs Insights query syntax
• Generate log summaries and identify error patterns
• Correlate logs across multiple AWS services
• Provide optimized tools suitable for AI assistants like Claude

Full feature list

📦 Installation

Prerequisites

• uv Python package and project manager
• An AWS account with the CloudWatch Logs service enabled
• Configured AWS credentials

Setup

# Clone the repository
git clone https://github.com/awslabs/Log-Analyzer-with-MCP.git
cd Log-Analyzer-with-MCP

# Create a virtual environment and install dependencies
uv sync
source .venv/bin/activate  # Use `.venv\Scripts\activate` on Windows

🚀 Quick Start

1. Ensure that you have configured your AWS credentials as described here.

2. Update the claude_desktop_config.json file to match the correct configuration described in the AI Integration Guide.

3. Open the Claude desktop app and start chatting!

For more examples and advanced usage, refer to the Detailed Usage Guide.

🤖 AI Integration

This project can be easily integrated with AI assistants such as the Claude desktop app. Check the AI Integration Guide for detailed information.

📚 Documentation

• Detailed Features
• Usage Guide
• AWS Configuration
• Architecture Details
• AI Integration
• Troubleshooting

🔒 Security

For more information, see CONTRIBUTING.

📄 License

This project is licensed under the Apache-2.0 license.