analyzeQueryPerformance

WHAT IT DOES

What analyzeQueryPerformance does on CloudWatch Application Signals MCP Server

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

THE RISK

Low Risk

Why analyzeQueryPerformance needs a policy

This tool performs static or performance analysis of CQL queries without side effects. It retrieves or computes analysis results about query characteristics. No data is modified, deleted, executed, or created. This is a Read operation with low blast radius - misuse would only result in incorrect performance metrics being returned, not data loss or unauthorized access.

From the tool's definition Tool name 'analyzeQueryPerformance' and description 'Analyzes the performance characteristics of a CQL query' indicate a query analysis operation.

Documented attack patterns abuse exactly the kind of access analyzeQueryPerformance gives an agent:

POLICY

How to control analyzeQueryPerformance

PolicyLayer is an MCP gateway — it sits between your AI agents and CloudWatch Application Signals MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for analyzeQueryPerformance:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "analyzeQueryPerformance": {}
  }
}

analyzeQueryPerformance is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register CloudWatch Application Signals MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

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EXPLORE

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Go deeper

Roll out MCP under one policy → Per-person scoped tokens, one central policy, and full audit across every server your team connects.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about analyzeQueryPerformance

What does the analyzeQueryPerformance tool do? +

Analyzes the performance characteristics of a CQL query - args: keyspace, query. It is categorised as a Read tool in the CloudWatch Application Signals MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on analyzeQueryPerformance? +

Register the CloudWatch Application Signals MCP Server MCP server in PolicyLayer and add a rule for analyzeQueryPerformance: 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 CloudWatch Application Signals MCP Server. Nothing to install.

What risk level is analyzeQueryPerformance? +

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

Can I rate-limit analyzeQueryPerformance? +

Yes. Add a rate_limit block to the analyzeQueryPerformance 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 analyzeQueryPerformance completely? +

Set action: deny in the PolicyLayer policy for analyzeQueryPerformance. 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 analyzeQueryPerformance? +

analyzeQueryPerformance is provided by the CloudWatch Application Signals MCP Server MCP server (awslabs.cloudwatch-applicationsignals-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every CloudWatch Application Signals MCP Server tool call.

Start from CloudWatch Application Signals MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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805 CloudWatch Application Signals MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.