Log Analyzer with MCP

A Model Context Protocol (MCP) server that provides AI assistants access to AWS CloudWatch Logs for analysis, searching, and correlation.

🏗️ Architecture

🔌 Model Context Protocol (MCP)

As outlined by Anthropic:

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

This repository is an example client and server that allows an AI assistant like Claude to interact with CloudWatch logs in an AWS account. To learn more about MCP, read through the introduction.

✨ Features

Browse 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
AI-optimized tools for assistants like Claude

Detailed feature list

🚀 Installation

Prerequisites

The uv Python package and project manager
An AWS account with CloudWatch Logs
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  # On Windows, use `.venv\Scripts\activate`

🚦 Quick Start

Make sure to have configured your AWS credentials as described here
Update your claude_desktop_config.json file with the proper configuration outlined in the AI integration guide
Open Claude for Desktop and start chatting!

For more examples and advanced usage, see the detailed usage guide.