AI agents use complete_youtube_oauth to create or update resources in PersonalizationMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your PersonalizationMCP environment.
This tool completes an OAuth2 flow and stores/writes authentication tokens for YouTube. It creates/writes credentials, which is a Write operation. It does not merely read data nor does it execute destructive or financial actions. Severity is medium because obtaining OAuth tokens grants the AI agent access to act on behalf of the user on YouTube.
From the tool's definition 完成YouTube OAuth2认证（获取令牌） — 'complete OAuth2 authentication (obtain token)'
Documented attack patterns abuse exactly the kind of access complete_youtube_oauth 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 complete_youtube_oauth:
{
"version": "1",
"default": "deny",
"tools": {
"complete_youtube_oauth": {
"limits": [
{
"counter": "complete_youtube_oauth_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}complete_youtube_oauth stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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完成YouTube OAuth2认证（获取令牌）. It is categorised as a Write tool in the PersonalizationMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Personalization MCP server in PolicyLayer and add a rule for complete_youtube_oauth: 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.
complete_youtube_oauth is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the complete_youtube_oauth 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 complete_youtube_oauth. 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.
complete_youtube_oauth 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.