Review draft memory batches and perform idempotent batch actions. Batch listing enforces the Phase 1 cap (target 3-5, hard cap 5). Approved suggestions remain review-state only in this phase; durable writes stay in the existing memory tools. Undo is pre-promotion only in Phase 1.
AI agents call review_memory_suggestions to retrieve information from Context Engine MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool is fundamentally a read operation that reviews draft data in a staging state. It explicitly delegates actual write operations to other tools (add_memory, etc.) and maintains an internal review state with phase-limited visibility. The 'undo is pre-promotion only' clause further confirms that this tool operates on unapproved, reversible suggestions rather than persistent data modifications.
From the tool's definition The tool performs 'review' of draft memory batches and enforces listing caps. The description explicitly states 'Approved suggestions remain review-state only' and 'durable writes stay in the existing memory tools,' indicating this tool only reviews and does…
Documented attack patterns abuse exactly the kind of access review_memory_suggestions gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Context Engine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for review_memory_suggestions:
{
"version": "1",
"default": "deny",
"tools": {
"review_memory_suggestions": {}
}
}review_memory_suggestions is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Review draft memory batches and perform idempotent batch actions. Batch listing enforces the Phase 1 cap (target 3-5, hard cap 5). Approved suggestions remain review-state only in this phase; durable writes stay in the existing memory tools. Undo is pre-promotion only in Phase 1. It is categorised as a Read tool in the Context Engine MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Context Engine MCP Server MCP server in PolicyLayer and add a rule for review_memory_suggestions: 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 Context Engine MCP Server. Nothing to install.
review_memory_suggestions is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the review_memory_suggestions 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.
Set action: deny in the PolicyLayer policy for review_memory_suggestions. 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.
review_memory_suggestions is provided by the Context Engine MCP Server MCP server (kirachon/context-engine). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Context Engine MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.