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Each Review agent has a dedicated management interface where you can monitor everything it has done, understand the value it’s generating, and control how it behaves going forward.

Agent Activity

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The Activity section shows a real-time feed of every action your Review agent has performed — PR reviews triggered, findings posted, policies evaluated, and communications sent. Each entry shows:
  • The action performed (e.g. PR review triggered, Finding posted, Policy evaluated)
  • The repository and PR it relates to
  • The timestamp of when it happened
The feed updates in real time as the agent works. You don’t need to refresh — new activity appears as it happens, giving you a live view of exactly what your agent is doing across all its assigned repositories.

Agent Work

The Work section surfaces two key metrics that help you quantify the value your Review agent delivers.

Actions Executed

The total number of discrete actions the agent has taken — PR reviews run, findings generated, policy checks completed. A direct measure of agent output.

Estimated Time Worked

An estimate of the cumulative time the agent has spent working, based on the complexity and volume of actions executed. Use this to calculate ROI against your team’s review time.
These metrics accumulate over the agent’s lifetime and give you a concrete basis for evaluating what automation is saving your team. If your agent has run 200 PR reviews and the estimated time worked is 40 hours, that’s 40 hours your engineers didn’t spend on manual review.

Token Usage

The Tokens section gives you full transparency into how many tokens your Review agent is consuming and how that usage breaks down by tool. You’ll see:
  • Total tokens used — cumulative token consumption across all agent activity
  • Breakdown by tool — token usage split by each review function the agent runs (e.g. Security Deep Dive, Infra Changes Review, Perf and Cost Review)
This breakdown lets you see which review functions are the most resource-intensive and make informed decisions about which to keep enabled based on the value they provide relative to their cost.

MCP Server

Every Review agent gets its own individual MCP (Model Context Protocol) server. This allows you to connect the agent directly to AI coding tools like Claude Code, Cursor, or any other MCP-compatible environment.
Each agent has its own isolated MCP server. This is intentional — it increases security by ensuring that access to one agent’s context does not expose another agent’s repositories or findings.

Enable or disable MCP access

From the agent management interface, you can toggle the MCP server on or off at any time.
  • Enabled — the agent is reachable via MCP. Use the provided endpoint to connect it to Claude Code, Cursor, or other tools.
  • Disabled — the MCP server is inactive. The agent continues to run PR reviews and post findings, but cannot be reached via MCP.

Connecting your agent

Once enabled, copy the MCP endpoint from the agent management interface and add it to your tool’s MCP configuration. The agent becomes available as a live collaborator — you can ask it about findings, query its review history, and use it as context during development.
Add the agent’s MCP endpoint to your Claude Code MCP configuration. Once connected, you can reference the agent’s findings and review history directly from your editor.

Function Management

The Functions tab shows the review functions currently assigned to the agent and lets you add or remove them at any time.
FunctionWhat it does
PR Security Deep DiveAnalyzes pull requests for security vulnerabilities, insecure patterns, and risky dependencies introduced by AI-generated code
PR Infra Changes ReviewReviews infrastructure-as-code changes in PRs — Terraform, Kubernetes manifests, Docker files, and more
PR Perf and Cost ReviewFlags performance inefficiencies and cost-impact changes introduced in the PR
PR Maintainability ReviewSurfaces code that will be hard to understand, test, or modify over time
PR Test and Quality GatesChecks test coverage, quality gates, and whether the PR meets defined testing standards before merge
Master PR ReviewA comprehensive review that combines all of the above into a single pass
Click Edit Functions to modify the assigned review types. Check or uncheck functions, then save.
Function changes take effect on the next incoming request. PRs already in progress will complete with the previous function set. New PRs opened after you save will use the updated configuration.

What’s next

Review Overview

Understand what your Review agent tracks and surfaces on every PR.

Creating Agents

Create a new Review agent or review the setup steps.