How to Use the Camunda (BPMN Engine) MCP in Mastra AI

Build resilient, automated workflows with Mastra AI and the Camunda (BPMN Engine) MCP Server.

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Connect Camunda (BPMN Engine) MCP to Mastra AI

Create your Vinkius account to connect Camunda (BPMN Engine) 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 Camunda (BPMN Engine) with Mastra AI

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Automated workflow logic with Mastra AI

Mastra AI agents use `activate_jobs` and `complete_job` to handle high-volume processing tasks automatically. You set the rules and the agent executes them against your engine. When a job fails, the agent uses `fail_job` to trigger your defined error handling logic. It keeps your operations moving without manual restarts.

Handling incidents with Mastra AI agents

Your agent monitors for production issues by calling `search_incidents` on a schedule. It pulls the details with `get_incident` to decide if it needs to intervene or alert a human. This keeps your system health high by catching errors early. The agent acts like a tireless operator watching your process topology.

Multi-tenancy and user management in Mastra AI

Use `search_tenants` and `search_users` to scope your agent's actions correctly. This ensures your Mastra AI workflow only touches the resources it is authorized to manage. It makes building secure, partition-aware agents simple. You define the boundary and the tools follow it.

Setup guide

Set up Camunda (BPMN Engine) 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 Camunda (BPMN Engine) 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: "camunda-bpmn-engine-mcp-client",
  servers: {
    "camunda-bpmn-engine-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about Camunda (BPMN Engine) MCP in Mastra AI

You list the tools in your agent definition and Mastra AI handles the execution flow. The agent calls the tools whenever the workflow logic requires process data.

Absolutely, you can chain these tools into any step of your Mastra AI workflow. It handles the state and the tool calls automatically.

Mastra AI handles retries natively, while the server provides the `fail_job` and `throw_job_error` tools to signal status. You combine these to build robust error recovery.

You call the MCP client's listTools method within your agent configuration. It automatically discovers all 25 operations provided by the engine.

Your XML definitions and process instances are protected by your unique endpoint token. The MCP Server transmits this sensitive business logic only over TLS-encrypted channels.

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