Suggest learning resources based on topic and student level.
AI agents call suggest_learning_resources to retrieve information from MedAdapt Content Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and recommends existing learning resources without creating, modifying, deleting, or executing anything. It is a pure information retrieval function, analogous to search or list operations. Severity is low because misuse (e.g., recommending inappropriate resources) has no irreversible consequences, no code execution, and no access to financial systems.
From the tool's definition Tool name 'suggest_learning_resources' and description indicate retrieval and recommendation of educational content. No modification, deletion, code execution, or financial operations are performed.
Documented attack patterns abuse exactly the kind of access suggest_learning_resources gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MedAdapt Content Server, and nothing reaches the server without passing your rules. This is the rule we recommend for suggest_learning_resources:
{
"version": "1",
"default": "deny",
"tools": {
"suggest_learning_resources": {}
}
}suggest_learning_resources is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Suggest learning resources based on topic and student level. It is categorised as a Read tool in the MedAdapt Content Server MCP Server, which means it retrieves data without modifying state.
Register the MedAdapt Content Server MCP server in PolicyLayer and add a rule for suggest_learning_resources: 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 MedAdapt Content Server. Nothing to install.
suggest_learning_resources 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 suggest_learning_resources 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 suggest_learning_resources. 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.
suggest_learning_resources is provided by the MedAdapt Content Server MCP server (ryoureddy/medadapt-content-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MedAdapt Content 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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7 MedAdapt Content Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.