Get enhanced recommendations using learning and knowledge graph
AI agents call memory_enhanced_recommendation to retrieve information from Documcp without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and generates recommendations by querying an internal learning model and knowledge graph. No data is created, modified, deleted, or used to trigger external actions. It is a read-only intelligence operation that returns suggestions to inform decision-making, not to execute or modify state.
From the tool's definition Tool description indicates it 'Get[s] enhanced recommendations using learning and knowledge graph' — a retrieval and analysis operation with no side effects.
Documented attack patterns abuse exactly the kind of access memory_enhanced_recommendation gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Documcp, and nothing reaches the server without passing your rules. This is the rule we recommend for memory_enhanced_recommendation:
{
"version": "1",
"default": "deny",
"tools": {
"memory_enhanced_recommendation": {}
}
}memory_enhanced_recommendation is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get enhanced recommendations using learning and knowledge graph. It is categorised as a Read tool in the Documcp MCP Server, which means it retrieves data without modifying state.
Register the Docu MCP server in PolicyLayer and add a rule for memory_enhanced_recommendation: 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 Documcp. Nothing to install.
memory_enhanced_recommendation 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 memory_enhanced_recommendation 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 memory_enhanced_recommendation. 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.
memory_enhanced_recommendation is provided by the Docu MCP server (tosin2013/documcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Documcp, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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52 Documcp tools catalogued and risk-classified — across an index of 43,000+ MCP servers.