Get comments on a LinkedIn post. Returns cleaned data in TOON format.
AI agents call get_post_comments to retrieve information from LinkedIn MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries existing comments from a LinkedIn post without creating, modifying, deleting, or executing any operations. It has no side effects beyond data retrieval. The blast radius of misuse is minimal—an attacker could enumerate comments or gather intelligence, but cannot alter LinkedIn data or trigger external operations. Classified as Read with low severity.
From the tool's definition Tool name 'get_post_comments' and description 'Get comments on a LinkedIn post' indicate data retrieval with no modification capability. Returns cleaned data for read-only access.
Attacks that exploit this kind of access
Get comments on a LinkedIn post. Returns cleaned data in TOON format. It is categorised as a Read tool in the LinkedIn MCP Server MCP Server, which means it retrieves data without modifying state.
Register the LinkedIn MCP Server MCP server in PolicyLayer and add a rule for get_post_comments: 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 LinkedIn MCP Server. Nothing to install.
get_post_comments 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_post_comments 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_post_comments. 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_post_comments is provided by the LinkedIn MCP Server MCP server (jing-yilin/linkedin-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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