youtube_schedule_video
현재 비공개인 내 영상의 향후 공개 예약을 미리 봅니다. 최소 1분 뒤 시각과 confirmVisible=true가 있어야 적용합니다. 한 번 공개된 영상은 YouTube가 예약을 거부합니다.
This record as markdown: /tools/yoonion-mimi-seed-mcp/youtube-schedule-video.md
What youtube_schedule_video does on Mimi Seed
AI agents use youtube_schedule_video to create or update resources in Mimi Seed, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mimi Seed environment.
Why youtube_schedule_video is rated Medium
Modifies video visibility schedule on YouTube; reversible but affects content publication timing.
From the tool's definition schedule video, reserve future publication, minimum 1 minute ahead
Attacks that exploit this kind of access
The rule that runs youtube_schedule_video safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mimi Seed, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For youtube_schedule_video, this is the rule to start with:
youtube_schedule_video 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Mimi Seed, apply this rule, and every youtube_schedule_video call is checked against it from then on.
Questions about youtube_schedule_video
현재 비공개인 내 영상의 향후 공개 예약을 미리 봅니다. 최소 1분 뒤 시각과 confirmVisible=true가 있어야 적용합니다. 한 번 공개된 영상은 YouTube가 예약을 거부합니다. It is categorised as a Write tool in the Mimi Seed MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mimi Seed MCP server in PolicyLayer and add a rule for youtube_schedule_video: 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 Mimi Seed. Nothing to install.
youtube_schedule_video 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 youtube_schedule_video 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 youtube_schedule_video. 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.
youtube_schedule_video is provided by the Mimi Seed MCP server (@yoonion/mimi-seed-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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