AI agents use pr_reviewers to create or update resources in Pr Review — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Pr Review environment.
This tool writes/modifies PR metadata by adding or removing reviewer assignments. It does not delete data irreversibly or execute code, but it does change the state of a PR in a reversible way. Misuse could disrupt review workflows or grant/remove review access inappropriately.
From the tool's definition "Request or remove reviewers on a PR" — modifies reviewer assignments on a pull request
Attacks that exploit this kind of access
Request or remove reviewers on a PR. It is categorised as a Write tool in the Pr Review MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Pr Review MCP server in PolicyLayer and add a rule for pr_reviewers: 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 Pr Review. Nothing to install.
pr_reviewers 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 pr_reviewers 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 pr_reviewers. 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.
pr_reviewers is provided by the Pr Review MCP server (thebtf/pr-review-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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