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Amazon CloudWatch Logs MCP Server

Created By
hyorimitsu8 months ago
A Model Context Protocol (MCP) server that enables AI assistants to interact with Amazon CloudWatch Logs through a standardized interface using AWS SDK.
Content

Amazon CloudWatch Logs MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with Amazon CloudWatch Logs services. This server enables AI assistant to manage CloudWatch logs through a standardized interface using AWS SDK.

License: MIT

Note: This project is currently under active development and not yet ready for production use. Features and APIs may change significantly before the first stable release.

Overview

This MCP server allows AI assistant to interact with Amazon CloudWatch Logs through the Model Context Protocol. It provides a standardized interface for performing various CloudWatch Logs operations, enabling comprehensive management and monitoring of log data.

Setup

Using Local Development Build

# Clone the repository
git clone https://github.com/hyorimitsu/mcp-amazon-cloud-watch-logs.git
cd mcp-amazon-cloud-watch-logs

# Install dependencies
pnpm install

# Build the project
pnpm run build

Configuration

To use the MCP server, you need to configure it with your AWS credentials. You can do this by setting environment variables:

{
  "mcpServers": {
    "amazon-cloudwatch-logs": {
      "command": "node",
      "args": ["/path/to/mcp-amazon-cloud-watch-logs/build/index.js"],
      "env": {
        "AWS_REGION": "us-east-1",
        "AWS_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY>",
        "AWS_SECRET_ACCESS_KEY": "<YOUR_SECRET_KEY>"
      }
    }
  }
}

Note: In the future, this project will be published as an npm package and as a Docker image for easier installation and usage.

Available Tools

Tool NameDescription
create_log_groupCreates a new Amazon CloudWatch Logs log group
describe_log_groupsList and describe Amazon CloudWatch Logs log groups
delete_log_groupDelete an Amazon CloudWatch Logs log group
create_log_streamCreate a new log stream in an Amazon CloudWatch Logs log group
describe_log_streamsList and describe log streams in an Amazon CloudWatch Logs log group
delete_log_streamDelete a log stream in an Amazon CloudWatch Logs log group
put_log_eventsWrite log events to a specified log stream in Amazon CloudWatch Logs
get_log_eventsRetrieve log events from a specified log stream in Amazon CloudWatch Logs
filter_log_eventsSearch log events with a pattern across log groups and streams in Amazon CloudWatch Logs

For detailed documentation on each tool, including parameters and examples, see TOOLS.md.

Note: This project is under development. Additional CloudWatch Logs operations are planned for future releases.

Development

This project uses VS Code Dev Containers for development to ensure a consistent development environment across all contributors.

Prerequisites for Development

Development Setup

  1. Clone the repository:

    git clone https://github.com/hyorimitsu/mcp-amazon-cloud-watch-logs.git
    cd mcp-amazon-cloud-watch-logs
    
  2. Open the project in VS Code:

    code .
    
  3. When prompted, click "Reopen in Container" or use the command palette and select "Dev Containers: Reopen in Container".

  4. VS Code will build the dev container and open the project inside it. This may take a few minutes the first time.

  5. Once inside the container, the development environment is fully set up with all dependencies installed.

Development Commands

All commands are run inside the dev container:

# Build the project
pnpm run build

# Run linter
pnpm run lint

# Fix linting issues
pnpm run lint:fix

# Format code
pnpm run format

# Test with the MCP Inspector
pnpm run inspector

Extending the Server

The server is designed to be easily extensible. To add a new CloudWatch Logs operation:

  1. Create a schema in src/operations/schemas/
  2. Implement the operation in src/operations/
  3. Add the tool definition to src/handlers/tools/types.ts
  4. Add the tool to the tools list in src/handlers/tools/tools.ts

License

This project is licensed under the MIT License - see the LICENSE file for details.

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