add_learning · Planning System MCP Server MCP: Risk & Policy

WHAT IT DOES

What add_learning does on Planning System MCP Server

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

WHY IT NEEDS A POLICY

Why add_learning needs a policy

An AI agent can call add_learning faster than any human can review — one bad instruction and it creates or modifies resources in Planning System MCP Server by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

add_learning Rate-limited

add_learning 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": {
    "add_learning": {
      "limits": [
        {
          "counter": "add_learning_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 Planning System MCP Server, so you can run agents against it safely.

FAQ

Questions about add_learning

What does the add_learning tool do? +

Record a knowledge episode. Use after research, on decisions, or when discovering. It is categorised as a Write tool in the Planning System 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 add_learning? +

Register the Planning System MCP Server MCP server in PolicyLayer and add a rule for add_learning: 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 Planning System MCP Server. Nothing to install.

What risk level is add_learning? +

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

Can I rate-limit add_learning? +

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

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

add_learning is provided by the Planning System MCP Server MCP server (tagents/agent-planner-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.