AI agents call get_user_saved_episodes to retrieve information from PersonalizationMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves personal data (saved podcast episodes) from the user's account without creating, modifying, or deleting any data. It is a pure read operation. While it accesses personal information, the severity is low because the data retrieved is user-owned metadata about saved content rather than sensitive credentials or high-impact information, and there are no irreversible consequences from reading it.
From the tool's definition Tool name 'get_user_saved_episodes' and description 'Get user's saved podcast episodes' indicate a retrieval operation with no modification or side effects.
Documented attack patterns abuse exactly the kind of access get_user_saved_episodes gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PersonalizationMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for get_user_saved_episodes:
{
"version": "1",
"default": "deny",
"tools": {
"get_user_saved_episodes": {}
}
}get_user_saved_episodes is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get user's saved podcast episodes. It is categorised as a Read tool in the PersonalizationMCP MCP Server, which means it retrieves data without modifying state.
Register the Personalization MCP server in PolicyLayer and add a rule for get_user_saved_episodes: 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 PersonalizationMCP. Nothing to install.
get_user_saved_episodes 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 get_user_saved_episodes 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 get_user_saved_episodes. 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.
get_user_saved_episodes is provided by the Personalization MCP server (yangliangwei/personalizationmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 88 PersonalizationMCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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88 PersonalizationMCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.