How to Use the Drone CI MCP in Mastra AI

Q: How do I implement human-in-the-loop for Drone CI in Mastra AI?

You set requireToolApproval: true for sensitive tools like approvebuild. This forces the agent to pause and wait for your manual confirmation before it executes the action.

Q: Can Mastra AI manage multiple Drone CI projects at once?

Absolutely. Your agents can call getcurrentuserrepos to map out all active projects. It then iterates through them to perform status checks or config updates.

Automate complex CI/CD workflows in Mastra AI. Handle build failures and secret updates with custom logic.

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Connect Drone CI MCP to Mastra AI

Create your Vinkius account to connect Drone CI 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 Drone CI with Mastra AI

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Claude

Perplexity

Conditional pipeline automation

Build agent workflows that use `list_builds` to monitor state and branch based on results. If a build fails, your Mastra agent can automatically trigger a `restart_build` or notify your team. This lets you define complex logic that handles common pipeline issues. You aren't just running scripts; you're building an autonomous operator for your deployments.

Infrastructure as code management

Use `create_secret` and `update_repo` to manage your environment programmatically. It keeps your CI/CD setup consistent across all your repositories. Your agent maintains the state of your Drone CI configuration. It ensures that changes are applied correctly, reducing the chance of human error during manual updates.

Reliable workflow execution

Mastra AI handles retries and failures, which is vital when calling `promote_build`. If a network hiccup occurs, the agent retries the operation automatically. This MCP Server acts as the bridge between your agent's decision-making and your build infrastructure. It keeps your pipeline moving even when things get messy.

Setup guide

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

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

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

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Common questions about Drone CI MCP in Mastra AI

You set `requireToolApproval: true` for sensitive tools like `approve_build`. This forces the agent to pause and wait for your manual confirmation before it executes the action.

Absolutely. Your agents can call `get_current_user_repos` to map out all active projects. It then iterates through them to perform status checks or config updates.

It is, provided you use the built-in approval gates. You define which tools your agents can use, effectively creating a sandbox for your CI/CD operations.

The server processes requests as they come in. If you have a massive build volume, you should ensure your Drone runner capacity is scaled to match the agent's activity.

The agent can read your build history, step logs, and repository settings. We isolate this access to specific API tokens, ensuring the agent only touches what you explicitly permit.

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