linkedin_add_comment

Add a comment to a LinkedIn post. Use post_id from search results or thread data.

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

Medium RISK CLASS

Category Write

Parameters 22 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/linkedin-add-comment.md

WHAT IT DOES

What linkedin_add_comment does on Dialogbrain

AI agents use linkedin_add_comment 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 text to post
`post_id`	string	Yes	LinkedIn post/activity ID (from search results or thread metadata)

Parameters from the server's own tool schema.

RISK

Why linkedin_add_comment is rated Medium

This tool creates new data (a comment) on LinkedIn, which is a reversible action. It does not delete data (Destructive), execute arbitrary code (Execute), or move money (Financial).

From the tool's definition Tool name is 'linkedin_add_comment' and description states 'Add a comment to a LinkedIn post', which is a create/modify action that adds new content to a social platform.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs linkedin_add_comment 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 linkedin_add_comment, this is the rule to start with:

linkedin_add_comment Rate-limited

linkedin_add_comment 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": {
    "linkedin_add_comment": {
      "limits": [
        {
          "counter": "linkedin_add_comment_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 linkedin_add_comment call is checked against it from then on.

FAQ

Questions about linkedin_add_comment

What does the linkedin_add_comment tool do? +

Add a comment to a LinkedIn post. Use post_id from search results or thread data. 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 linkedin_add_comment accept? +

linkedin_add_comment accepts 2 parameters: text, post_id. Required: text, post_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on linkedin_add_comment? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for linkedin_add_comment: 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 linkedin_add_comment? +

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

Can I rate-limit linkedin_add_comment? +

Yes. Add a rate_limit block to the linkedin_add_comment 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 linkedin_add_comment completely? +

Set action: deny in the PolicyLayer policy for linkedin_add_comment. 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 linkedin_add_comment? +

linkedin_add_comment 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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