What is Log Analyzer With Mcp

Log-Analyzer-with-MCP is a Model Context Protocol (MCP) server that enables AI assistants to access and analyze AWS CloudWatch Logs for searching and correlation.

Use cases

Use cases include troubleshooting application errors, monitoring system performance, analyzing user activity logs, and enhancing AI assistant capabilities for log-related queries.

How to use

To use Log-Analyzer-with-MCP, clone the repository, set up your AWS credentials, and configure the AI integration. Then, you can browse and search CloudWatch Log Groups and generate log summaries.

Key features

Key features include browsing and searching CloudWatch Log Groups, using CloudWatch Logs Insights query syntax, generating log summaries, identifying error patterns, and correlating logs across multiple AWS services.

Where to use

Log-Analyzer-with-MCP is primarily used in cloud computing environments, particularly for applications that require log analysis and monitoring in AWS.

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

1. Make sure to have configured your AWS credentials as described here

2. Update your claude_desktop_config.json file with the proper configuration outlined in the AI integration guide

3. Open Claude for Desktop and start chatting!

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

🤖 AI Integration

This project can be easily integrated with AI assistants like Claude for Desktop. See the AI integration guide for details.

📚 Documentation

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

🔒 Security

See CONTRIBUTING for more information.

📄 License

This project is licensed under the Apache-2.0 License.