store_memory

A write tool on the CogniRepo MCP server.

SERVERCogniRepo SOURCEpypi:cognirepo

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade A, identity unverified Pull the record →

This record as markdown: /tools/ashlesh-t-cognirepo/store-memory.md

WHAT IT DOES

What store_memory does on CogniRepo

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

RISK

Why store_memory is rated Medium

The name 'store_memory' strongly suggests a write operation — persisting data (likely memory/context) to storage. This aligns with the server's stated purpose of 'persistent memory and context for AI tools.' Since the description is empty, confidence is reduced, but the name and server context together suggest a reversible write (store/create) rather than anything more severe.

From the tool's definition Tool name 'store_memory' implies creating or saving data to persistent memory storage.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs store_memory safely

PolicyLayer is an MCP gateway: it sits between your AI agents and CogniRepo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For store_memory, this is the rule to start with:

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.

The button opens the PolicyLayer dashboard: create your workspace, connect CogniRepo, apply this rule, and every store_memory call is checked against it from then on.

FAQ

Questions about store_memory

What does the store_memory tool do? +

store_memory is a write tool on the CogniRepo MCP server. It is categorised as a Write tool in the CogniRepo 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 CogniRepo 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 CogniRepo. 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 CogniRepo MCP server (pypi:cognirepo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

More on CogniRepo, and thousands of servers like it.

This server

All 34 CogniRepo tools →

Across the catalogue

team_manager_write_memory on Team Manager MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →