youtube_post_comment_reply

Post a comment on a YouTube video, or reply to an existing comment. Pass video_id for a top-level comment, OR parent_comment_id to reply. AI-disclosure suffix appended automatically when configured.

SERVERDialogbrain SOURCEhttps://api.dialogbrain.com/mcp

Medium RISK CLASS

Category Write

Parameters 31 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-saloprj-dialogbrain/youtube-post-comment-reply.md

WHAT IT DOES

What youtube_post_comment_reply does on Dialogbrain

AI agents use youtube_post_comment_reply to create or update resources in Dialogbrain, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dialogbrain environment.

Parameter	Type	Required	Description
`text`	string	Yes	Comment body. 1-10000 chars. AI-disclosure suffix may be auto-appended.
`video_id`	string	—	Bare videoId or 'youtube:video:<id>' — for a top-level comment.
`parent_comment_id`	string	—	Bare commentId or 'youtube:comment:<id>' — for a reply.

Parameters from the server's own tool schema.

RISK

Why youtube_post_comment_reply is rated Medium

This tool creates new comments on YouTube, which is reversible (comments can be deleted). It modifies external state but does not execute arbitrary code, delete data, or move money. The medium severity reflects potential for abuse (spam, harassment, misleading AI-generated comments) but limited blast radius since individual comments have bounded impact.

From the tool's definition Tool description states 'Post a comment on a YouTube video, or reply to an existing comment' — these are write operations that create new data (comments) on an external platform.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs youtube_post_comment_reply safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For youtube_post_comment_reply, this is the rule to start with:

youtube_post_comment_reply Rate-limited

youtube_post_comment_reply 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "youtube_post_comment_reply": {
      "limits": [
        {
          "counter": "youtube_post_comment_reply_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Dialogbrain, apply this rule, and every youtube_post_comment_reply call is checked against it from then on.

FAQ

Questions about youtube_post_comment_reply

What does the youtube_post_comment_reply tool do? +

Post a comment on a YouTube video, or reply to an existing comment. Pass video_id for a top-level comment, OR parent_comment_id to reply. AI-disclosure suffix appended automatically when configured. It is categorised as a Write tool in the Dialogbrain MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does youtube_post_comment_reply accept? +

youtube_post_comment_reply accepts 3 parameters: text, video_id, parent_comment_id. Required: text. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on youtube_post_comment_reply? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for youtube_post_comment_reply: 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 Dialogbrain. Nothing to install.

What risk level is youtube_post_comment_reply? +

youtube_post_comment_reply is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit youtube_post_comment_reply? +

Yes. Add a rate_limit block to the youtube_post_comment_reply 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.

How do I block youtube_post_comment_reply completely? +

Set action: deny in the PolicyLayer policy for youtube_post_comment_reply. 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.

What MCP server provides youtube_post_comment_reply? +

youtube_post_comment_reply is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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