memory_pruning

THE RISK

Critical Risk

Why memory_pruning needs a policy

Memory pruning typically involves permanently deleting or removing stored information to optimize space/performance. The term 'pruning' implies irreversible deletion rather than modification. However, the description is minimal ('Intelligent memory pruning and optimization'), so the exact behavior is uncertain.

From the tool's definition 'memory pruning' - pruning implies removal/deletion of stored data; 'optimization' suggests irreversible cleanup of memory/state

Documented attack patterns abuse exactly the kind of access memory_pruning gives an agent:

POLICY

How to control memory_pruning

PolicyLayer is an MCP gateway — it sits between your AI agents and Documcp, and nothing reaches the server without passing your rules. This is the rule we recommend for memory_pruning:

policy.json

{
  "version": "1",
  "default": "deny",
  "hide": [
    "memory_pruning"
  ]
}

memory_pruning disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.

Create a free account and register Documcp — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RESTRICT THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Documcp tools

Destructive cleanup_agent_artifacts Detect, classify, and clean up artifacts generated by AI coding agents (e.g., TODO.md, PLA Destructive memory_cleanup Clean up old memories Execute change_watcher Watch code changes and trigger documentation drift detection in near real-time. Execute deploy_pages [DEPRECATED — use deploy_site instead] Set up GitHub Pages deployment workflow. This alias Execute deploy_site Set up deployment workflow for GitHub Pages or Vercel with deployment tracking and prefere Execute memory_migration Create and execute migration plans between different memory systems Execute test_local_deployment Test documentation build and local server before deploying to GitHub Pages Write optimize_readme Optimize README content by restructuring, condensing, and extracting detailed sections to

All 52 Documcp tools →

Destructive tools on other servers

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Go deeper

Critical-risk tools in Documcp → Every critical-risk tool this server exposes, in one view.
All critical-risk MCP tools → Every critical-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Blast radius → How much damage one compromised or confused agent can do — and how to bound it.
Tool call approval → Approval gates on individual tool calls: auto-allow, prompt, or deny.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about memory_pruning

What does the memory_pruning tool do? +

Intelligent memory pruning and optimization. It is categorised as a Destructive tool in the Documcp MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on memory_pruning? +

Register the Docu MCP server in PolicyLayer and add a rule for memory_pruning: 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 Documcp. Nothing to install.

What risk level is memory_pruning? +

memory_pruning is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit memory_pruning? +

Yes. Add a rate_limit block to the memory_pruning 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 memory_pruning completely? +

Set action: deny in the PolicyLayer policy for memory_pruning. 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 memory_pruning? +

memory_pruning is provided by the Docu MCP server (tosin2013/documcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Documcp tool call.

Start from Documcp, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →