Log-Analyzer-with-MCP
A Model Context Protocol (MCP) server that provides AI assistants access to AWS CloudWatch Logs for analysis, searching, and correlation
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123
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Forks
18
Issues
5
Installation
Difficulty
IntermediateEstimated Time
10-20 minutes
Requirements
uv: latest versionAWS account with CloudWatch Logs enabled+1 more
Installation
Installation
Prerequisites
uv: Latest version
AWS Account: With CloudWatch Logs enabled
AWS Credentials: Configured
Installation Steps
1. Clone Repository
bash
git clone https://github.com/awslabs/Log-Analyzer-with-MCP.git
cd Log-Analyzer-with-MCP
2. Install Dependencies
``bash
uv sync
source .venv/bin/activate # On Windows, use .venv\Scripts\activate
``
Troubleshooting
Common Issues
Issue: Server won't start Solution: Check Node.js version and reinstall dependencies. Issue: Not recognized by Claude Desktop Solution: Verify configuration file path and syntax.Configuration
Configuration
Basic Configuration
Claude Desktop Setup
Edit~/.config/claude-desktop/claude_desktop_config.json (macOS/Linux) or
%APPDATA%\Claude\claude_desktop_config.json (Windows):
json
{
"mcpServers": {
"log-analyzer": {
"command": "python",
"args": ["-m", "server"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Environment Variables
Set the following environment variables as needed:bash
export API_KEY="your-api-key"
export DEBUG="true"
Configuration Example
json
{
"mcpServers": {
"log-analyzer": {
"command": "python",
"args": ["-m", "server"],
"env": {
"PORT": "3000",
"LOG_LEVEL": "info"
}
}
}
}
Examples
Examples
Basic Usage
Using with Claude Desktop
1Verify MCP Server Startup
Open Claude Desktop and confirm that the configuration has been loaded correctly.
2Execute Basic Commands
Available tools from this MCP server:
- log-analyzer: Analyze logs from CloudWatch
Programmatic Usage
python
import requests
import json
def call_mcp_tool(tool_name, params):
response = requests.post(
'http://localhost:3000/mcp/call',
json={
'tool': tool_name,
'parameters': params
}
)
return response.json()
Usage example
result = call_mcp_tool('analyze', {
'input': 'sample data',
'options': {'format': 'json'}
})
Use Cases
Search for specific error messages in AWS CloudWatch Logs to identify the root cause of issues.
Correlate logs from multiple AWS services to analyze overall system performance.
Utilize AI assistants to analyze trends from historical log data and predict future issues.
Automate regular log analysis to provide real-time insights to operational teams.