AI agents call get_memory_usage to retrieve information from Redis without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves metadata about a Redis key's memory consumption without modifying, executing code, or triggering external operations. It is a pure informational query with no side effects, making it a Read category tool with low severity.
From the tool's definition Tool name 'get_memory_usage' and description indicate retrieval of memory statistics for a key. No modification, deletion, or execution of arbitrary code.
Attacks that exploit this kind of access
获取键的内存使用量. It is categorised as a Read tool in the Redis MCP Server, which means it retrieves data without modifying state.
Register the Redis MCP server in PolicyLayer and add a rule for get_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 Redis. Nothing to install.
get_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 get_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 get_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.
get_memory_usage is provided by the Redis MCP server (lm203688/redis-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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