Fetch all inline and general review comments authored by a user within a time range, filtered by repository. Returns structured JSON with PR-level grouping, total PRs reviewed, total comments, user ID, date range, and for each PR: array of comment bodies and total comments count. Automatically fi...
AI agents call github.getReviewComments to retrieve information from GitHub 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 historical GitHub review comment data for analysis purposes. It performs no write operations, does not execute code or commands, does not delete data, and has no financial impact. The filtering and grouping are read-only operations. The use cases (counting, analyzing patterns, tracking) are all analytical and non-destructive.
From the tool's definition Tool description states it 'Fetch[es]' and 'Returns structured JSON' with no modification, creation, deletion, or execution capabilities. Verbs used: 'Fetch', 'Returns', 'Analyze', 'filters' (read-only filtering).
Attacks that exploit this kind of access
Fetch all inline and general review comments authored by a user within a time range, filtered by repository. Returns structured JSON with PR-level grouping, total PRs reviewed, total comments, user ID, date range, and for each PR: array of comment bodies and total comments count. Automatically filters out auto-generated comments and comments on auto-created PRs. All comment bodies are properly JSON-escaped. Use this tool to analyze review comment quality and quantity. Example use cases: - Count review comments to assess review thoroughness - Analyze comment patterns across different PRs - Track review engagement metrics - Extract review feedback for analysis Returns: Object with userId, dateRange, totalPRsReviewed, totalComments, and array of PR objects (each with prId, prNumber, prTitle, prRepo, prUrl, prCreatedAt, comments array, totalComments). It is categorised as a Read tool in the GitHub MCP Server MCP Server, which means it retrieves data without modifying state.
Register the GitHub MCP Server MCP server in PolicyLayer and add a rule for github.getReviewComments: 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 MCP Server. Nothing to install.
github.getReviewComments 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 github.getReviewComments 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 github.getReviewComments. 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.
github.getReviewComments is provided by the GitHub MCP Server MCP server (radireddy/github-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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