@hyorimitsu
基本信息
A Model Context Protocol (MCP) server that enables AI assistants to interact with Amazon CloudWatch Logs through a standardized interface using AWS SDK.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-amazon-cloudwatch-logs": {
"command": "docker",
"args": [
"pull",
"ghcr.io/hyorimitsu/mcp-amazon-cloudwatch-logs:latest"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
A Model Context Protocol (MCP) server that provides tools for interacting with Amazon CloudWatch Logs services. It enables AI assistants to manage CloudWatch logs through a standardized interface using the AWS SDK.
Install globally via npm (npm install -g @hyorimitsu/amazon-cloudwatch-logs-mcp-server) or pull the Docker image (ghcr.io/hyorimitsu/mcp-amazon-cloudwatch-logs:latest). Then add the server to your AI assistant’s configuration, setting the required environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY, and optionally AWS_REGION and READONLY.
It provides a set of tools for AI assistants to interact with Amazon CloudWatch Logs, including creating, describing, and deleting log groups and streams, putting and retrieving log events, and running CloudWatch Logs Insights queries.
You need an AWS account with CloudWatch Logs access, an AWS access key and secret key with appropriate permissions, and either Node.js (for npm) or Docker installed.
No. The project is actively under development and not yet ready for production. Features and APIs may change before the first stable release.
Set the `READONLY` environment variable to `"true"` in the server configuration. This disables all write operations (create, modify, delete) while keeping read operations available.
Yes. Pull the image from `ghcr.io/hyorimitsu/mcp-amazon-cloudwatch-logs:latest` and configure your AI assistant to run it as a Docker container with the required AWS environment variables.
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