Get Bilibili user's favorite folders and videos.
AI agents call get_bilibili_favorites 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 favorite data from Bilibili without creating, modifying, or deleting content. It is a read-only operation. Severity is medium rather than low because it accesses personal user data (favorites), which could expose preferences or usage patterns if misused by an AI agent without proper authorization or context.
From the tool's definition Tool name 'get_bilibili_favorites' and description 'Get Bilibili user's favorite folders and videos' indicate retrieval of existing data with no modifications or deletions.
Documented attack patterns abuse exactly the kind of access get_bilibili_favorites 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_bilibili_favorites:
{
"version": "1",
"default": "deny",
"tools": {
"get_bilibili_favorites": {}
}
}get_bilibili_favorites is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get Bilibili user's favorite folders and videos. 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_bilibili_favorites: 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_bilibili_favorites 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_bilibili_favorites 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_bilibili_favorites. 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_bilibili_favorites 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.