Low Risk

kage_recall

Recall repo-local Kage memory from .agent_memory packets. Returns an agent-ready context block plus ranked packet summaries.

How to control kage_recall ↓

What kage_recall does on Kage

AI agents call kage_recall 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_recall needs a policy

The tool retrieves stored memory packets and returns them as read-only context. There are no side effects, modifications, or executions described — it simply queries and returns ranked summaries of existing memory data.

From the tool's definition Recall repo-local Kage memory from .agent_memory packets. Returns an agent-ready context block plus ranked packet summaries.

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

How to control kage_recall

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_recall:

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

kage_recall 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_recall

What does the kage_recall tool do? +

Recall repo-local Kage memory from .agent_memory packets. Returns an agent-ready context block plus ranked packet summaries. 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_recall? +

Register the Kage MCP server in PolicyLayer and add a rule for kage_recall: 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_recall? +

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

Can I rate-limit kage_recall? +

Yes. Add a rate_limit block to the kage_recall 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_recall completely? +

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

kage_recall 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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