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AI agents use add_comment to create or update resources in Preloop — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Preloop environment.
An AI agent can call add_comment faster than any human can review — one bad instruction and it creates or modifies resources in Preloop by the hundred, each call as confident as the last.
Documented attack patterns abuse exactly the kind of access add_comment gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Preloop, and nothing reaches the server without passing your rules. This is the rule we recommend for add_comment:
{
"version": "1",
"default": "deny",
"tools": {
"add_comment": {
"limits": [
{
"counter": "add_comment_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}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.
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Add a comment to an issue, pull request, or merge request. For general comments: provide just target and comment. For inline code comments: also provide path and line. To reply to a thread: provide in_reply_to with the comment ID. It is categorised as a Write tool in the Preloop MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Preloop MCP server in PolicyLayer and add a rule for 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 Preloop. Nothing to install.
add_comment 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 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.
Set action: deny in the PolicyLayer policy for 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.
add_comment is provided by the Preloop MCP server (preloop/preloop). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 15 Preloop tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
15 Preloop tools catalogued and risk-classified — across an index of 42,500+ MCP servers.