store_memory · Personal RAG MCP Server MCP: Risk & Policy

WHAT IT DOES

What store_memory does on Personal RAG MCP Server

AI agents use store_memory to create or update resources in Personal RAG MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Personal RAG MCP Server environment.

WHY IT NEEDS A POLICY

Why store_memory needs a policy

The name 'store_memory' strongly suggests this tool writes or persists data (notes, documents, snippets) into a memory/RAG store. Given the server context of storing personal notes and documents, this is a Write operation. Severity is medium because an AI agent misusing this could pollute the personal knowledge base with incorrect or malicious content. Confidence is reduced due to the empty description.

From the tool's definition Tool name 'store_memory' implies writing/storing data; description is empty and provides no additional detail.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

store_memory Rate-limited

store_memory stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

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

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Personal RAG MCP Server, so you can run agents against it safely.

FAQ

Questions about store_memory

What does the store_memory tool do? +

store_memory. It is categorised as a Write tool in the Personal RAG MCP Server 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 Personal RAG MCP Server 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 Personal RAG MCP Server. 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 Personal RAG MCP Server MCP server (timerickson/personal-rag-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.