performance.monitor_memory_usage
Track memory consumption patterns during execution
This record as markdown: /tools/jrmatherly-mcp-context-forge/performance.monitor-memory-usage.md
What performance.monitor_memory_usage does on ContextForge MCP Gateway
AI agents call performance.monitor_memory_usage to retrieve information from ContextForge MCP Gateway without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why performance.monitor_memory_usage is rated Low
This tool retrieves and queries memory consumption data as a monitoring/observability function. It has no side effects, does not execute code or commands, does not modify state, and does not involve financial operations. It fits squarely in the Read category as an informational/diagnostic capability. The blast radius of misuse is minimal—an AI agent could only extract performance telemetry, which presents low risk.
From the tool's definition Tool name 'monitor_memory_usage' and description 'Track memory consumption patterns during execution' indicate passive observation/monitoring of system metrics with no modification, creation, deletion, or execution of external operations.
Attacks that exploit this kind of access
The rule that runs performance.monitor_memory_usage safely
PolicyLayer is an MCP gateway: it sits between your AI agents and ContextForge MCP Gateway, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For performance.monitor_memory_usage, this is the rule to start with:
performance.monitor_memory_usage is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect ContextForge MCP Gateway, apply this rule, and every performance.monitor_memory_usage call is checked against it from then on.
Questions about performance.monitor_memory_usage
Track memory consumption patterns during execution. It is categorised as a Read tool in the ContextForge MCP Gateway MCP Server, which means it retrieves data without modifying state.
Register the ContextForge MCP Gateway MCP server in PolicyLayer and add a rule for performance.monitor_memory_usage: 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 ContextForge MCP Gateway. Nothing to install.
performance.monitor_memory_usage 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 performance.monitor_memory_usage 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 performance.monitor_memory_usage. 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.
performance.monitor_memory_usage is provided by the ContextForge MCP Gateway MCP server (jrmatherly/mcp-context-forge). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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