Low Risk

kage_decisions

Summarize Kage why-memory for a repo: decisions, gotchas, runbooks, conventions, code explanations, path coverage, weak/stale memory, and important code paths that still lack decision memory.

How to control kage_decisions ↓

What kage_decisions does on Kage

AI agents call kage_decisions to retrieve information from Kage without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why kage_decisions needs a policy

This tool reads and summarizes existing memory/documentation stored in the Kage system. It retrieves decisions, runbooks, conventions and coverage information without creating, modifying, or deleting any data. Pure read/query operation with low blast radius if misused.

From the tool's definition Summarize Kage why-memory for a repo: decisions, gotchas, runbooks, conventions, code explanations, path coverage, weak/stale memory

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

How to control kage_decisions

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "kage_decisions": {}
  }
}

kage_decisions is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

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

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Questions about kage_decisions

What does the kage_decisions tool do? +

Summarize Kage why-memory for a repo: decisions, gotchas, runbooks, conventions, code explanations, path coverage, weak/stale memory, and important code paths that still lack decision memory. It is categorised as a Read tool in the Kage MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on kage_decisions? +

Register the Kage MCP server in PolicyLayer and add a rule for kage_decisions: 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 Kage. Nothing to install.

What risk level is kage_decisions? +

kage_decisions is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit kage_decisions? +

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

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

kage_decisions is provided by the Kage MCP server (@kage-core/kage-graph-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Kage tool call.

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

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62 Kage tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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