Lambda Performance MCP Server (Node.js)
A comprehensive Model Context Protocol (MCP) server for analyzing AWS Lambda performance, tracking cold starts, and providing optimization recommendations. Built with Node.js and the AWS SDK v3.
Features
Performance Analysis
- Comprehensive Metrics: Duration, memory usage, error rates, invocation counts
- Cold Start Tracking: Detailed analysis of cold start patterns and frequency
- Real-time Monitoring: Live performance metrics and alerts
- Cost Analysis: Detailed cost breakdown and optimization opportunities
Advanced Analytics
- Percentile Analysis: P50, P90, P95, P99 duration metrics
- Memory Utilization: Right-sizing recommendations based on actual usage
- Error Pattern Analysis: Identify and categorize error types
- Trend Analysis: Performance trends over time
Optimization Recommendations
- Cold Start Optimization: Provisioned concurrency, package size, initialization
- Memory Right-sizing: Optimal memory allocation based on usage patterns
- Cost Optimization: ARM architecture, duration optimization, resource efficiency
- Performance Tuning: Code optimization, connection pooling, caching strategies
Comparative Analysis
- Multi-function Comparison: Compare performance across multiple Lambda functions
- Benchmarking: Identify best and worst performers
- Resource Utilization: Compare memory, duration, and cost metrics
Installation
- Clone the repository:
git clone <repository-url>
cd lambda-performance-mcp-nodejs
- Install dependencies:
npm install
- Configure environment:
cp .env.example .env
# Edit .env with your AWS credentials and configuration
- Set up AWS credentials:
# Option 1: Environment variables
export AWS_ACCESS_KEY_ID=your_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_key
export AWS_REGION=us-east-1
# Option 2: AWS CLI profile
aws configure --profile lambda-analyzer
export AWS_PROFILE=lambda-analyzer
# Option 3: IAM roles (for EC2/Lambda execution)
Required AWS Permissions
The MCP server requires the following AWS permissions:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"lambda:ListFunctions",
"lambda:GetFunction",
"lambda:GetFunctionConfiguration",
"cloudwatch:GetMetricStatistics",
"cloudwatch:GetMetricData",
"logs:FilterLogEvents",
"logs:DescribeLogGroups",
"logs:DescribeLogStreams"
],
"Resource": "*"
}
]
}
Usage
Running the MCP Server
# Start the server
npm start
# Development mode with auto-reload
npm run dev
Available Tools
1. Analyze Lambda Performance
{
"name": "analyze_lambda_performance",
"arguments": {
"functionName": "my-lambda-function",
"timeRange": "24h",
"includeDetails": true
}
}
2. Track Cold Starts
{
"name": "track_cold_starts",
"arguments": {
"functionName": "my-lambda-function",
"timeRange": "24h"
}
}
3. Get Optimization Recommendations
{
"name": "get_optimization_recommendations",
"arguments": {
"functionName": "my-lambda-function",
"analysisType": "all"
}
}
4. Compare Lambda Performance
{
"name": "compare_lambda_performance",
"arguments": {
"functionNames": ["function-1", "function-2", "function-3"],
"timeRange": "24h",
"metrics": ["duration", "cold-starts", "errors", "cost"]
}
}
5. List Lambda Functions
{
"name": "list_lambda_functions",
"arguments": {
"runtime": "nodejs18.x",
"includeMetrics": true
}
}
6. Analyze Memory Utilization
{
"name": "analyze_memory_utilization",
"arguments": {
"functionName": "my-lambda-function",
"timeRange": "24h"
}
}
7. Get Cost Analysis
{
"name": "get_cost_analysis",
"arguments": {
"functionName": "my-lambda-function",
"timeRange": "30d"
}
}
8. Monitor Real-time Performance
{
"name": "monitor_real_time_performance",
"arguments": {
"functionName": "my-lambda-function",
"duration": 5
}
}
Configuration with MCP Clients
To use this MCP server with MCP clients, add it to your MCP configuration:
Workspace Configuration (.mcp/settings/mcp.json)
{
"mcpServers": {
"lambda-performance": {
"command": "node",
"args": ["path/to/lambda-performance-mcp-nodejs/index.js"],
"env": {
"AWS_REGION": "us-east-1",
"AWS_ACCESS_KEY_ID": "your_access_key",
"AWS_SECRET_ACCESS_KEY": "your_secret_key"
},
"disabled": false,
"autoApprove": [
"list_lambda_functions",
"analyze_lambda_performance",
"track_cold_starts"
]
}
}
}
Global Configuration (~/.mcp/settings/mcp.json)
{
"mcpServers": {
"lambda-performance": {
"command": "node",
"args": ["path/to/lambda-performance-mcp-nodejs/index.js"],
"env": {
"AWS_PROFILE": "default"
},
"disabled": false
}
}
}
Key Features Explained
Cold Start Analysis
- Pattern Detection: Identifies when and why cold starts occur
- Duration Analysis: Tracks initialization times and optimization opportunities
- Trigger Identification: Determines what causes cold starts (idle time, scaling, deployments)
- Timeline Visualization: Shows cold start frequency over time
Performance Optimization
- Memory Right-sizing: Analyzes actual memory usage vs. allocated memory
- Duration Optimization: Identifies performance bottlenecks and optimization opportunities
- Cost Optimization: Provides recommendations to reduce Lambda costs
- Architecture Recommendations: Suggests ARM vs x86 based on workload compatibility
Real-time Monitoring
- Live Metrics: Current invocation rates, duration, and error rates
- Performance Alerts: Automatic detection of performance issues
- Activity Tracking: Recent invocation history and patterns
Example Outputs
Performance Analysis
# Lambda Performance Analysis: my-function
## Summary
- **Total Invocations**: 15,432
- **Average Duration**: 245ms
- **Cold Start Rate**: 12.3%
- **Error Rate**: 0.8%
- **Memory Utilization**: 67%
## Performance Metrics
- **P50 Duration**: 180ms
- **P95 Duration**: 450ms
- **P99 Duration**: 890ms
- **Max Duration**: 1,200ms
## Cold Start Analysis
- **Total Cold Starts**: 1,898
- **Average Cold Start Duration**: 1,200ms
- **Cold Start Pattern**: Moderate frequency during low traffic
Optimization Recommendations
# Optimization Recommendations: my-function
## Priority Recommendations
1. **Right-size Memory Allocation** (Impact: High)
- Current memory is over-provisioned
- Implementation: Reduce memory from 512MB to 256MB
- Expected Improvement: Reduce costs by 25%
2. **Optimize Cold Start Performance** (Impact: High)
- High cold start rate detected
- Implementation: Implement provisioned concurrency for 2-3 instances
- Expected Improvement: Reduce cold starts by 85%
Troubleshooting
Common Issues
-
Permission Errors
- Ensure AWS credentials have required permissions
- Check CloudWatch Logs access for cold start analysis
-
No Data Available
- Verify function name is correct
- Check if function has been invoked in the specified time range
- Ensure CloudWatch logging is enabled
-
Connection Timeouts
- Check AWS region configuration
- Verify network connectivity to AWS services
Debug Mode
# Enable debug logging
export LOG_LEVEL=debug
npm start
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
Support
For issues and questions:
- Check the troubleshooting section
- Review AWS permissions
- Verify environment configuration
- Check CloudWatch Logs for detailed error messages