Medium Risk

store_memory

Store a fact, preference, decision, observation, or rule in persistent memory. Survives session restarts. Deduplicates automatically. Set importance (1-10) and optional TTL.

Risk signalsAccepts raw HTML/template content (content) · High parameter count (10 properties)

Part of the Memoryoracle server.

store_memory can modify Memoryoracle data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use store_memory to create or modify resources in Memoryoracle. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call store_memory repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Memoryoracle.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "store_memory": {
      "limits": [
        {
          "counter": "store_memory_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Memoryoracle policy for all 10 tools.

Get this rule live on your own Memoryoracle server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access store_memory gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so store_memory only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the store_memory tool do? +

Store a fact, preference, decision, observation, or rule in persistent memory. Survives session restarts. Deduplicates automatically. Set importance (1-10) and optional TTL.. It is categorised as a Write tool in the Memoryoracle MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on store_memory? +

Register the Memoryoracle 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 Memoryoracle. Nothing to install.

What risk level is store_memory? +

store_memory is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit store_memory? +

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.

How do I block store_memory completely? +

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.

What MCP server provides store_memory? +

store_memory is provided by the Memoryoracle MCP server (https://tooloracle.io/memory/mcp/). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Memoryoracle tool call.

Deterministic rules across all 10 Memoryoracle tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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