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Lambda Performance MCP Server

by jghidalgo
OverviewInspectNewSchemaRelated ServersScore
JavaScript
Remote

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

  1. Clone the repository:

git clone <repository-url> cd lambda-performance-mcp-nodejs

  1. Install dependencies:

npm install

  1. Configure environment:

cp .env.example .env # Edit .env with your AWS credentials and configuration

  1. 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

  1. Permission Errors

    • Ensure AWS credentials have required permissions

    • Check CloudWatch Logs access for cold start analysis

  2. No Data Available

    • Verify function name is correct

    • Check if function has been invoked in the specified time range

    • Ensure CloudWatch logging is enabled

  3. Connection Timeouts

    • Check AWS region configuration

    • Verify network connectivity to AWS services

Debug Mode

# Enable debug logging export LOG_LEVEL=debug npm start

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests if applicable

  5. 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

Deploy Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

How are these scores calculated?

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