Compare your game library with a friend's library to find common games.
AI agents call compare_games_with_friend 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 is fundamentally a read operation that queries personal game library data from Steam (or similar) and performs a comparison. While it accesses personal data and could reveal private information (gaming habits, library contents), it does not create, modify, delete, or execute code.
From the tool's definition Tool description states 'Compare your game library with a friend's library to find common games' — retrieves and compares game library data between two parties without modifying or deleting anything.
Documented attack patterns abuse exactly the kind of access compare_games_with_friend 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 compare_games_with_friend:
{
"version": "1",
"default": "deny",
"tools": {
"compare_games_with_friend": {}
}
}compare_games_with_friend is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Compare your game library with a friend's library to find common games. 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 compare_games_with_friend: 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.
compare_games_with_friend 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 compare_games_with_friend 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 compare_games_with_friend. 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.
compare_games_with_friend 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.
Free to start. No card required.
88 PersonalizationMCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.