Log Analyzer with CloudWatch Logs

by awslabs

4 stars

316 downloads

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GitHub

About

Provides structured access to CloudWatch Logs data for searching, analyzing, and correlating logs across AWS services to help with troubleshooting and pattern identification.

Details

Author: awslabs
Repository: awslabs/Log-Analyzer-with-MCP
GitHub stars: 4
Downloads: 316
License: Apache License 2.0
Categories: Developer Tools, Design, Workplace, AI, Search, Cloud Service, Communication, Infrastructure, Frontend

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name Log Analyzer with CloudWatch Logs

Command (node, npx, python, etc.) npx
Arguments
- Argument 1 -y
- Argument 2 @highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "/c",
                "npx",
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "cmd"
        }
    }
}

JSON

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "log analyzer with cloudwatch logs": {
            "env": {},
            "args": [
                "-y",
                "@highlight/mcp-server"
            ],
            "command": "npx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Macos

{
    "env": [],
    "args": [
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "npx"
}

Windows

{
    "env": [],
    "args": [
        "/c",
        "npx",
        "-y",
        "@highlight/mcp-server"
    ],
    "command": "cmd"
}

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

Detailed feature list

🚀 Installation

Prerequisites

- The uv Python package and project manager (includes uvx)
- An AWS account with CloudWatch Logs
- Configured AWS credentials

🚦 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.2a:["$","div",null,{"classNa

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

Linux

Macos

Windows

Log Analyzer with MCP

🏗️ Architecture

🔌 Model Context Protocol (MCP)

✨ Features

🚀 Installation

Prerequisites

🚦 Quick Start

🤖 AI Integration

📚 Documentation

🔒 Security

📄 License

Install

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