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https://github.com/awslabs/log-analyzer-with-mcp

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

https://github.com/awslabs/log-analyzer-with-mcp

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Repository

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

Basic Info
  • Host: GitHub
  • Owner: awslabs
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 348 KB
Statistics
  • Stars: 113
  • Watchers: 6
  • Forks: 17
  • Open Issues: 5
  • Releases: 0
Created about 1 year ago · Last pushed 11 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

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

```bash

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

🔒 Security

See CONTRIBUTING for more information.

📄 License

This project is licensed under the Apache-2.0 License.

Owner

  • Name: Amazon Web Services - Labs
  • Login: awslabs
  • Kind: organization
  • Location: Seattle, WA

AWS Labs

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Dependencies

pyproject.toml pypi
  • boto3 >=1.37.11
  • mcp [cli]>=1.3.0
uv.lock pypi
  • annotated-types 0.7.0
  • anyio 4.8.0
  • boto3 1.37.11
  • botocore 1.37.11
  • certifi 2025.1.31
  • click 8.1.8
  • colorama 0.4.6
  • h11 0.14.0
  • httpcore 1.0.7
  • httpx 0.28.1
  • httpx-sse 0.4.0
  • idna 3.10
  • jmespath 1.0.1
  • log-analyzer-with-mcp 0.1.0
  • markdown-it-py 3.0.0
  • mcp 1.3.0
  • mdurl 0.1.2
  • pydantic 2.10.6
  • pydantic-core 2.27.2
  • pydantic-settings 2.8.1
  • pygments 2.19.1
  • python-dateutil 2.9.0.post0
  • python-dotenv 1.0.1
  • rich 13.9.4
  • ruff 0.9.10
  • s3transfer 0.11.4
  • shellingham 1.5.4
  • six 1.17.0
  • sniffio 1.3.1
  • sse-starlette 2.2.1
  • starlette 0.46.1
  • typer 0.15.2
  • typing-extensions 4.12.2
  • urllib3 2.3.0
  • uvicorn 0.34.0