How to Use the Gerrit MCP in Mastra AI

Q: How can I use Mastra AI to automate my Gerrit code review process?

You build a workflow. Your Mastra AI agent can use querychanges to find pending reviews and listreviewers to see if they're assigned, then trigger notifications based on your own logic.

Build resilient, multi-step Gerrit workflows with Mastra AI's TypeScript-native agent framework.

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Connect Gerrit MCP to Mastra AI

Create your Vinkius account to connect Gerrit to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Gerrit with Mastra AI

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Automate Code Review Checks

Stop babysitting pull requests. Build a Mastra AI workflow that uses `query_changes` to find all changes in a 'needs review' state. The agent can then loop through them, using `get_change` to check for specific labels or comments. Mastra's built-in retry logic means that if the Gerrit API hiccups, your workflow doesn't just fail. It waits and tries again. You can build a process that reliably checks review status and only notifies you when an action is truly needed.

Create Smart Gerrit Escalation Paths

Your agent can make decisions. A workflow can use `get_change` to check a review's age. If it's over 48 hours old, it runs `list_reviewers` to see who's assigned. If no one is, the workflow can escalate. This is where conditional logic shines. The workflow can then use other tools to page a team lead or file a ticket. This Gerrit MCP server gives your agent the facts it needs to trigger the right branch in your automation.

Run Audits with this MCP Server

You can automate compliance and health checks. Schedule a Mastra agent to run nightly. It can use `list_projects` and `list_branches` to check for stale branches or non-standard naming conventions. The agent can also use `list_groups` to make sure project permissions are correct, cross-referencing owners against an external source of truth. With Mastra's `requireToolApproval` feature, you can even have the agent propose actions that a human must confirm.

Setup guide

Set up Gerrit MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Gerrit tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "gerrit-mcp-client",
  servers: {
    "gerrit-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Gerrit Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Gerrit tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Gerrit transactions"
);
console.log(result.text);

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Common questions about Gerrit MCP in Mastra AI

You build a workflow. Your Mastra AI agent can use `query_changes` to find pending reviews and `list_reviewers` to see if they're assigned, then trigger notifications based on your own logic.

You don't have to. Mastra AI's workflow engine has automatic retries with exponential backoff, so temporary Gerrit connection issues won't break your automation.

Not with this toolset. It's designed for reading information—checking status with `get_change` or finding branches with `list_branches`. Writing actions like merging aren't included.

The MCP server handles authentication, provides a stable interface, and runs in a secure sandbox. You just give your agent a URL and it works, without managing API keys or client libraries in your code.

The server strictly handles Gerrit metadata. This includes change descriptions, patch set history, project configurations, and account details. It does not access or store your repository's source code.

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