How to Use the Dify.AI SDK MCP in Mastra AI

Q: Does the Dify.AI SDK work with Mastra AI branching?

It does. You can chain tools like runworkflow and chatmessage inside your agent sequences to create complex logic trees.

Build complex agents with Dify.AI SDK and Mastra AI. Automate multi-step workflows with built-in retry and branching logic.

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…and any MCP-compatible client

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Connect Dify.AI SDK MCP to Mastra AI

Create your Vinkius account to connect Dify.AI SDK 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 Dify.AI SDK with Mastra AI

Ask AI about this MCP

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Claude

Perplexity

Autonomous workflow branching

Use `run_workflow` to start complex processes. Mastra AI detects the output and handles conditional logic automatically if a step fails or requires a retry. Configure your agents to check `get_workflow_parameters` before starting. This ensures every trigger has the data it needs to succeed on the first attempt.

Advanced conversation management

Track long-running agent tasks using `get_conversations`. You can pull specific message history with `get_conversation_messages` to inform the agent's next move. If an agent gets stuck, `stop_chat_generation` allows you to kill the process immediately. It prevents wasted compute time on stale requests.

Feedback-driven agent improvement

Implement a human-in-the-loop system with `submit_feedback`. Your agents learn from these signals to adjust their logic for future iterations. Call `get_app_meta` to verify the agent's current configuration. It keeps your agent's internal state synced with the Dify platform settings.

Setup guide

Set up Dify.AI SDK 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 Dify.AI SDK 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: "difyai-sdk-mcp-client",
  servers: {
    "difyai-sdk-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dify.AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Dify.AI SDK MCP in Mastra AI

Yes. Use the MCPClient class to register the server tools. Mastra AI then treats these as native capabilities for your agents.

It does. You can chain tools like `run_workflow` and `chat_message` inside your agent sequences to create complex logic trees.

You add the server URL to your MCPClient configuration. Mastra AI handles the transport and tool registration automatically.

The server provides the hooks, and Mastra AI handles the retry intervals. You configure the backoff strategy in your agent definition.

The server isolates all conversation history and metadata. It uses token-based auth to ensure only your authorized agents can access sensitive interaction logs.

Use it with your favorite AI tools

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