List reviews on a pull request (each review may contain multiple inline comments — use get_pull_request_review_comments to fetch them).
AI agents call get_pull_request_reviews to retrieve information from Mcp Github without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves and lists pull request reviews, which is a read-only query operation. It has no capability to modify, create, delete, or execute actions. The blast radius is minimal as it only exposes existing review metadata that is typically already accessible to repository members.
From the tool's definition Tool description states 'List reviews on a pull request' — a query operation that retrieves existing data without modification or side effects.
Attacks that exploit this kind of access
List reviews on a pull request (each review may contain multiple inline comments — use get_pull_request_review_comments to fetch them). It is categorised as a Read tool in the Mcp Github MCP Server, which means it retrieves data without modifying state.
Register the Mcp Github MCP server in PolicyLayer and add a rule for get_pull_request_reviews: 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 Mcp Github. Nothing to install.
get_pull_request_reviews 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_pull_request_reviews 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_pull_request_reviews. 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_pull_request_reviews is provided by the Mcp Github MCP server (@missionsquad/mcp-github). 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.
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