Lambda Performance MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AWS_REGION | No | AWS region | |
| AWS_PROFILE | No | AWS CLI profile name | |
| AWS_ACCESS_KEY_ID | No | Your AWS access key ID | |
| AWS_SECRET_ACCESS_KEY | No | Your AWS secret access key |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_lambda_performanceC | Analyze Lambda function performance metrics including cold starts, duration, and errors |
| track_cold_startsC | Track and analyze cold start patterns for Lambda functions |
| get_optimization_recommendationsC | Get performance optimization recommendations for Lambda functions |
| compare_lambda_performanceB | Compare performance metrics between multiple Lambda functions |
| list_lambda_functionsC | List all Lambda functions in the account with basic performance info |
| analyze_memory_utilizationC | Analyze memory utilization and provide right-sizing recommendations |
| get_cost_analysisC | Analyze Lambda function costs and identify optimization opportunities |
| monitor_real_time_performanceC | Get real-time performance metrics and alerts for Lambda functions |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Most tools have distinct purposes, such as analyze_lambda_performance for general metrics, analyze_memory_utilization for memory-specific analysis, and compare_lambda_performance for comparisons. However, analyze_lambda_performance and monitor_real_time_performance could be confused, as both involve performance metrics, though one is general analysis and the other is real-time monitoring.
All tool names follow a consistent verb_noun pattern using snake_case, such as analyze_lambda_performance, list_lambda_functions, and track_cold_starts. This uniformity makes the tool set predictable and easy to understand.
With 8 tools, the server is well-scoped for Lambda performance analysis, covering key areas like monitoring, cost, optimization, and specific metrics. Each tool serves a clear purpose without being overwhelming or insufficient.
The tool set covers core aspects of Lambda performance analysis, including listing functions, analyzing metrics, cost, optimization, and cold starts. A minor gap is the lack of tools for configuration updates or direct action implementation, but agents can work around this by using recommendations from existing tools.