How to Use the Buildkite MCP in Mastra AI

Q: Can Mastra AI automatically retry a failed Buildkite build?

You can configure a workflow that calls rebuild if the initial getbuild status indicates a failure. It handles the logic without you needing to step in.

Build complex Mastra AI workflows that trigger Buildkite deployments and handle failures with automated retries.

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Connect Buildkite MCP to Mastra AI

Create your Vinkius account to connect Buildkite 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 Buildkite with Mastra AI

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Buildkite task automation for Mastra AI

Chain `create_build` with your custom business logic to automate your release cycle. If a build fails, your agent can catch the error and decide the next step. This setup allows for conditional branching based on the result of `get_build`. You define the logic once and let the agent run it.

Multi-step pipeline management

Use `list_pipelines` and `list_pipeline_builds` to feed data into your Mastra AI agents. They can compare current build states against your internal requirements. Your agents act as a control layer for your CI/CD. They can trigger a `rebuild` if they detect an issue in the previous execution.

Agent-driven infrastructure oversight

Query `list_agents` to monitor your build capacity during heavy load. Your agents can alert you if your runners are offline. It keeps your operations running smoothly without human intervention. The MCP server provides the data, and your agents take the necessary action.

Setup guide

Set up Buildkite 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 Buildkite 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: "buildkite-mcp-client",
  servers: {
    "buildkite-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Buildkite MCP in Mastra AI

You can configure a workflow that calls `rebuild` if the initial `get_build` status indicates a failure. It handles the logic without you needing to step in.

Add the server URL to your agent definition in your Mastra project. Once imported, the tools are ready to be used in your agent's task list.

They work well for that specific use case. The agent triggers the build and monitors the result, acting only when the pipeline state requires attention.

Your API tokens stay inside the Vinkius sandbox. Your agent only receives the specific data returned by the tools it invokes.

It processes organization, pipeline, and agent logs. This data is strictly limited to your CI/CD operational metrics and build history.

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