Store important information in persistent memory for later retrieval. Use this to remember key facts, decisions, code patterns, or any information that might be useful in future conversations.
AI agents use store_memory to create or update resources in AgentCortex MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AgentCortex MCP environment.
This tool writes data to a persistent memory store. It creates or modifies stored records but does not delete or execute anything. Misuse could result in storing incorrect, misleading, or sensitive information that persists across sessions and influences future AI behavior, making severity medium.
From the tool's definition 'Store important information in persistent memory' and 'remember key facts, decisions, code patterns, or any information that might be useful in future conversations'
Attacks that exploit this kind of access
Store important information in persistent memory for later retrieval. Use this to remember key facts, decisions, code patterns, or any information that might be useful in future conversations. It is categorised as a Write tool in the AgentCortex MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the AgentCortex MCP server in PolicyLayer and add a rule for store_memory: 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 AgentCortex MCP. Nothing to install.
store_memory is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the store_memory 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 store_memory. 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.
store_memory is provided by the AgentCortex MCP server (sage-hq/agentcortex-mcp). 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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