Low Risk

kage_memory_handoff

Return a teammate/agent handoff queue by combining memory inbox, lifecycle, audit, timeline, and lineage into concrete next actions.

How to control kage_memory_handoff ↓

What kage_memory_handoff does on Kage

AI agents call kage_memory_handoff 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_memory_handoff needs a policy

The tool retrieves and aggregates data from multiple memory sources (inbox, lifecycle, audit, timeline, lineage) to produce a handoff queue. It reads and compiles existing information without creating, modifying, or deleting anything. Severity is medium because the handoff queue could expose sensitive code context or architectural decisions to agents/teammates.

From the tool's definition Return a teammate/agent handoff queue by combining memory inbox, lifecycle, audit, timeline, and lineage into concrete next actions

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

How to control kage_memory_handoff

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_memory_handoff:

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

kage_memory_handoff 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_memory_handoff

What does the kage_memory_handoff tool do? +

Return a teammate/agent handoff queue by combining memory inbox, lifecycle, audit, timeline, and lineage into concrete next actions. 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_memory_handoff? +

Register the Kage MCP server in PolicyLayer and add a rule for kage_memory_handoff: 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_memory_handoff? +

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

Can I rate-limit kage_memory_handoff? +

Yes. Add a rate_limit block to the kage_memory_handoff 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_memory_handoff completely? +

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

kage_memory_handoff 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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