auto_learn_if_needed

THE RISK

High Risk

This tool automatically executes a learning/analysis process against the codebase when intelligence data is missing or stale. It triggers an external operation (codebase analysis and data ingestion) rather than simply reading existing data or writing a known record.

From the tool's definition 'Automatically learn from codebase' and 'Call this first before using other In-Memoria tools' — triggers an automated analysis/learning process on the codebase

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

HOW TO CONTROL AUTO_LEARN_IF_NEEDED

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

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "auto_learn_if_needed": {
      "limits": [
        {
          "counter": "auto_learn_if_needed_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

auto_learn_if_needed stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

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

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

More In Memoria tools

Execute learn_codebase_intelligence Build intelligence database from codebase (one-time setup, ~30-60s). Required before using Write contribute_insights Let AI agents save discovered insights (bug patterns, optimizations, best practices) back Read analyze_codebase One-time analysis of a specific file or directory. Returns AST structure, complexity metri Read get_developer_profile Get patterns and conventions learned from this codebase\ Read get_intelligence_metrics Get detailed metrics about the intelligence database and learning state Read get_pattern_recommendations Get coding pattern recommendations learned from this codebase. Use this when implementing Read get_performance_status Get performance metrics including database size, query times, and resource usage Read get_project_blueprint Get instant project blueprint - eliminates cold start exploration by providing tech stack,

All 14 In Memoria tools →

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Go deeper

High-risk tools in In Memoria → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-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.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

What does the auto_learn_if_needed tool do? +

Automatically learn from codebase if intelligence data is missing or stale. Call this first before using other In-Memoria tools - it\. It is categorised as a Execute tool in the In Memoria MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on auto_learn_if_needed? +

Register the In Memoria MCP server in PolicyLayer and add a rule for auto_learn_if_needed: 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 In Memoria. Nothing to install.

What risk level is auto_learn_if_needed? +

auto_learn_if_needed is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit auto_learn_if_needed? +

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

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

auto_learn_if_needed is provided by the In Memoria MCP server (pi22by7/in-memoria). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every In Memoria tool call.

Deterministic rules across all 14 In Memoria tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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// WHAT AUTO_LEARN_IF_NEEDED ON IN MEMORIA DOES

// THE RISK

// HOW TO CONTROL AUTO_LEARN_IF_NEEDED

// EXPLORE