GC efficiency from .jfr: pause time vs freed bytes per collector/cause. Use after stop_profiling; complements profile_memory and heap_info. Not a general JFR summary (see parse_jfr_summary).
Risk signalsAccepts file system path (filepath)
Part of the Javaperf server.
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AI agents call gc_efficiency to retrieve information from Javaperf without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though gc_efficiency only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"gc_efficiency": {}
}
}See the full Javaperf policy for all 26 tools.
These attack patterns abuse exactly the kind of access gc_efficiency gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
GC efficiency from .jfr: pause time vs freed bytes per collector/cause. Use after stop_profiling; complements profile_memory and heap_info. Not a general JFR summary (see parse_jfr_summary).. It is categorised as a Read tool in the Javaperf MCP Server, which means it retrieves data without modifying state.
Register the Javaperf MCP server in PolicyLayer and add a rule for gc_efficiency: 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 Javaperf. Nothing to install.
gc_efficiency 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 gc_efficiency 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 gc_efficiency. 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.
gc_efficiency is provided by the Javaperf MCP server (javaperf). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 26 Javaperf tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.