Log Analyzer with MCP

By awslabs GitHub

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

log-analyzer aws

Overview

what is Log Analyzer with MCP?

Log Analyzer with MCP is a server that enables AI assistants to access and analyze AWS CloudWatch Logs, facilitating searching and correlation of log data.

how to use Log Analyzer with MCP?

To use the Log Analyzer, clone the repository, set up your AWS credentials, and configure the AI assistant (like Claude) to interact with the logs.

key features of Log Analyzer with MCP?

Browse and search CloudWatch Log Groups
Utilize CloudWatch Logs Insights query syntax for searching
Generate summaries of logs and identify error patterns
Correlate logs across multiple AWS services
AI-optimized tools for seamless integration with assistants like Claude

use cases of Log Analyzer with MCP?

Analyzing application logs for error detection
Monitoring AWS service performance through log correlation
Assisting AI models in understanding log data for better insights

FAQ from Log Analyzer with MCP?

What is the Model Context Protocol (MCP)?

MCP is a standardized protocol that allows AI applications to connect with various data sources, similar to how USB-C connects devices.

Do I need an AWS account to use this project?

Yes, an AWS account with CloudWatch Logs is required to utilize the Log Analyzer.

Is there documentation available for setup and usage?

Yes, detailed documentation is provided in the repository, including installation, configuration, and usage guides.

Content

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

Architecture Diagram

🔌 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.