CloudWatch Logs MCP Server
Description
# CloudWatch Logs MCP Server An MCP (Model Context Protocol) server that provides tools for accessing AWS CloudWatch logs. This server allows AI assistants to list log groups and read log entries from AWS CloudWatch. ## Available Tools ### list_groups Lists available CloudWatch…
About
# CloudWatch Logs MCP Server An MCP (Model Context Protocol) server that provides tools for accessing AWS CloudWatch logs. This server allows AI assistants to list log groups and read log entries from AWS CloudWatch. ## Available Tools ### list_groups Lists available CloudWatch log groups. **Parameters:** - `prefix`…
Details
- Author
- serkanh
- GitHub stars
- 27
- Downloads
- 286
- Categories
- Cloud Service, Other, Infrastructure, Developer Tools
Jump to
- List available CloudWatch log groups with optional prefix.
- Read log entries from a specific log group.
- Filter logs by time (ISO or relative "5m", "1h", "1d"), log stream, and filter pattern.
- Support overriding AWS region and credentials per tool call.
- Returns JSON output with log group details or log events.
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
CloudWatch Logs MCP ServerCommand (node, npx, python, etc.)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
From the repository
Configure AWS credentials via environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY) or the AWS CLI. Then add the server to your Claude Desktop configuration (claude_desktop_config.json) using either a Python command or a Docker container. The server exposes two tools: list_groups and get_logs.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"cloudwatch logs mcp server": {
"cloudwatch-logs": {
"command": "python3",
"args": [
"/path/to/cloudwatch-logs-mcp/main.py"
],
"env": {
"AWS_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>",
"AWS_SECRET_ACCESS_KEY": "<YOUR_SECRET_ACCESS_KEY>"
},
"disabled": false,
"autoApprove": []
}
}
}
}McpServers
{
"cloudwatch-logs": {
"command": "python3",
"args": [
"/path/to/cloudwatch-logs-mcp/main.py"
],
"env": {
"AWS_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>",
"AWS_SECRET_ACCESS_KEY": "<YOUR_SECRET_ACCESS_KEY>"
},
"disabled": false,
"autoApprove": []
}
}Access AWS CloudWatch logs to list log groups and read log entries.
An MCP (Model Context Protocol) server that provides tools for accessing AWS CloudWatch logs. This server allows AI assistants to list log groups and read log entries from AWS CloudWatch.
- prefix(optional): Log group name prefix
- region(optional): AWS region
- accessKeyId(optional): AWS access key ID
- secretAccessKey(optional): AWS secret access key
- sessionToken(optional): AWS session token
Returns:JSON string with the list of log groups, includinglogGroupName,creationTime, andstoredBytes.
Gets CloudWatch logs from a specific log group.
- logGroupName(required): The name of the log group
- logStreamName(optional): The name of the log stream
- startTime(optional): Start time in ISO format or relative time (e.g., "5m", "1h", "1d")
- endTime(optional): End time in ISO format
- filterPattern(optional): Filter pattern for the logs
- region(optional): AWS region
- accessKeyId(optional): AWS access key ID
- secretAccessKey(optional): AWS secret access key
- sessionToken(optional): AWS session token
Returns:JSON string with the log events, includingtimestamp,message, andlogStreamName.
Ensure you have AWS credentials configured. You can set them up using the AWS CLI or by setting environment variables:
Add the following to yourclaude_desktop_config.json:
{ "mcpServers": { "cloudwatch-logs": { "command": "python3", "args": ["/path/to/cloudwatch-logs-mcp/main.py"], "env": { "AWS_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>", "AWS_SECRET_ACCESS_KEY": "<YOUR_SECRET_ACCESS_KEY>", }, "disabled": false, "autoApprove": [] } } }
If you prefer to run the server in a Docker container, you can set up a Dockerfile and use the following configuration:
{ "mcpServers": { "cloudwatch-logs": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "AWS_ACCESS_KEY_ID", "-e", "AWS_SECRET_ACCESS_KEY", "mcp/cloudwatch-logs" ], "env": { "AWS_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>", "AWS_SECRET_ACCESS_KEY": "<YOUR_SECRET_ACCESS_KEY>", } } } }
This server is built using the FastMCP class from the MCP SDK, which provides a simple way to create MCP servers. The server exposes two main tools:
- list_groups: Lists available CloudWatch log groups
- get_logs: Reads log entries from specific log groups
Each tool is implemented as an async function decorated with@mcp.tool(). The server uses the boto3 library to interact with the AWS CloudWatch Logs API.
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