analyze_memory_utilization

Analyze memory utilization and provide right-sizing recommendations

Server Lambda Performance MCP Server jghidalgo/lambda-performance-mcp-nodejs
Category Read
Risk class Low
Parameters 00 required

What analyze_memory_utilization does on Lambda Performance MCP Server

AI agents call analyze_memory_utilization to retrieve information from Lambda Performance MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why analyze_memory_utilization needs a policy

This tool queries AWS Lambda performance metrics and provides recommendations based on existing data. It retrieves and analyzes memory utilization patterns without modifying infrastructure, executing code, or causing side effects. The blast radius of misuse is minimal—an attacker could only access performance insights they likely already have visibility into through AWS console access.

From the tool's definition Tool name 'analyze_memory_utilization' and description 'Analyze memory utilization and provide right-sizing recommendations' indicate data retrieval and analysis. No modification, deletion, or execution of Lambda functions occurs.

Questions about analyze_memory_utilization

What does the analyze_memory_utilization tool do? +

Analyze memory utilization and provide right-sizing recommendations. It is categorised as a Read tool in the Lambda Performance MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on analyze_memory_utilization? +

Register the Lambda Performance MCP Server MCP server in PolicyLayer and add a rule for analyze_memory_utilization: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Lambda Performance MCP Server. Nothing to install.

What risk level is analyze_memory_utilization? +

analyze_memory_utilization is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit analyze_memory_utilization? +

Yes. Add a rate_limit block to the analyze_memory_utilization rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block analyze_memory_utilization completely? +

Set action: deny in the PolicyLayer policy for analyze_memory_utilization. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides analyze_memory_utilization? +

analyze_memory_utilization is provided by the Lambda Performance MCP Server MCP server (jghidalgo/lambda-performance-mcp-nodejs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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