How to Use the Juhe Data / 聚合数据 MCP in Mastra AI

Build reliable multi-step workflows with Juhe Data / 聚合数据 and the Mastra AI agent framework.

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Connect Juhe Data / 聚合数据 MCP to Mastra AI

Create your Vinkius account to connect Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 with Mastra AI

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Perplexity

Automated workflows with failure handling

Define complex sequences that use `get_exchange_rate` or `get_oil_price` within your agent workflows. Mastra handles retries automatically if an API call fails, keeping your logic running without manual intervention. If a step hits a rate limit or network error, the engine manages the backoff. You focus on the business logic while the server ensures the data reaches your workflow steps.

Branching logic for data-driven actions

Use the output from `get_calendar_day` to trigger conditional branches in your agent. If the tool returns a holiday status, your agent can route the task to a specific handler or skip it entirely. This allows you to build sophisticated agents that react to real-world conditions. Your agents act based on the data they retrieve, not just static instructions.

Human-in-the-loop tool execution

Toggle tool approval for sensitive operations like `get_id_card_info`. You can force the agent to pause until a human reviews the planned action, ensuring compliance with your internal security standards. This keeps you in control of critical lookups. You get the speed of automation with the safety of manual oversight for any tool that touches sensitive data.

Setup guide

Set up Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 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: "juhe-data-mcp-client",
  servers: {
    "juhe-data-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Juhe Data / 聚合数据 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 Juhe Data / 聚合数据. 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 Juhe Data / 聚合数据 MCP in Mastra AI

You instantiate an MCP client within your workflow. This allows your agents to call Juhe tools as part of their standard task execution path.

Absolutely. You can pass the output of one tool, like an IP address from `get_ip_lookup`, into another tool or a local function to build a full pipeline.

The server uses secure transport protocols. By enforcing tool approval for sensitive requests, you ensure that no PII is accessed without explicit verification.

Mastra provides built-in retry mechanisms. It will catch the error from the server and follow the backoff strategy you defined in your workflow engine.

It is straightforward. You provide the URL to your Mastra server configuration, and the framework auto-detects and registers the available tools for your agents.

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