Create a review on a pull request review
AI agents use create_pull_request_review to create or update resources in GitHub See MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GitHub See MCP Server environment.
Creating a pull request review modifies repository state by adding reviewer feedback, but the action is reversible and does not permanently destroy data or execute arbitrary code. It fits the Write category as it creates new data.
From the tool's definition Tool name 'create_pull_request_review' and description 'Create a review on a pull request review' indicate the tool creates/adds a new review entity on a pull request. This is a reversible write operation (reviews can be deleted or edited).
Attacks that exploit this kind of access
Create a review on a pull request review. It is categorised as a Write tool in the GitHub See MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GitHub See MCP Server MCP server in PolicyLayer and add a rule for create_pull_request_review: 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 GitHub See MCP Server. Nothing to install.
create_pull_request_review 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 create_pull_request_review 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 create_pull_request_review. 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.
create_pull_request_review is provided by the GitHub See MCP Server MCP server (jesusmaster/github-see-mcp-server). 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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