Analyze RxJS code for potential memory leaks and subscription management issues. Recognizes modern auto-cleanup patterns (takeUntilDestroyed, async pipe, useEffect cleanup, onUnmounted) to avoid false positives.
AI agents call detect_memory_leak to retrieve information from Rxjs without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool examines RxJS code for potential memory leak issues and identifies cleanup patterns. It reads and analyzes code structure without creating, modifying, deleting, or executing any code. The analysis is informational and non-destructive, making it a Read operation with low blast radius even if misused, as it cannot affect system state or data integrity.
From the tool's definition Tool performs static analysis of RxJS code to 'Analyze' and 'Recognizes' patterns without modifying code or executing side effects. The description indicates inspection/review functionality only.
Attacks that exploit this kind of access
Analyze RxJS code for potential memory leaks and subscription management issues. Recognizes modern auto-cleanup patterns (takeUntilDestroyed, async pipe, useEffect cleanup, onUnmounted) to avoid false positives. It is categorised as a Read tool in the Rxjs MCP Server, which means it retrieves data without modifying state.
Register the Rxjs MCP server in PolicyLayer and add a rule for detect_memory_leak: 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 Rxjs. Nothing to install.
detect_memory_leak is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the detect_memory_leak 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.
Set action: deny in the PolicyLayer policy for detect_memory_leak. 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.
detect_memory_leak is provided by the Rxjs MCP server (shuji-bonji/rxjs-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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