How to Use the Zetachain Explorer (ZetaChain Block Explorer API) MCP in Mastra AI

Q: How can Mastra AI use Zetachain Explorer (ZetaChain Block Explorer API) to validate asset ownership?

The workflow first checks for the token using gettoken. If found, it proceeds to check if an address is listed as a holder via gettokenholders. This two-step conditional process ensures high confidence in your data.

Q: What's the best process for analyzing contract calls using Zetachain Explorer (ZetaChain Block Explorer API) and Mastra AI?

Use gettransactioninternal within a workflow. You can build logic that says: 'If an internal call is made, then analyze its logs.' This sequence handles the full lifecycle of a contract interaction.

Q: How do I list and process recent data using Zetachain Explorer (ZetaChain Block Explorer API) with Mastra AI?

Start by calling listblocks to get the latest block hashes. Your workflow can then loop through these, running a specialized tool like getblocktransactions for each one until the desired time limit is reached.

Build reliable, self-correcting financial workflows with Mastra AI and Zetachain Explorer (ZetaChain Block Explorer API).

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Setup Zetachain Explorer (ZetaChain Block Explorer API) with Mastra AI

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Multi-Stage Asset Validation

Need to check if a token exists before tracking its transfers? You build this flow in Mastra AI. The workflow first calls `get_token` and checks the result. If successful, it conditionally proceeds to call `get_address_tokens`. This handles complex branching. The system automatically retries if the initial asset lookup fails due to a temporary network issue, ensuring your payment logic doesn't fail simply because of timing.

Deep Transaction Failure Analysis

When tracking a failing transaction, use `get_transaction_internal` and `get_transaction_logs`. The workflow can analyze these logs to determine the precise cause of failure. Mastra AI then triggers an admin notification if the error code falls outside expected parameters. This capability lets you automatically process complex failure scenarios—like a failed contract call—and manage the resolution without manual intervention.

Systematic Chain Auditing

To audit a time period, your workflow first calls `list_blocks` to determine the range of hashes. It then iterates over this list, calling `get_block_transactions` for each block hash. This systematic approach ensures no data is missed. This allows you to build an automated process that aggregates transaction counts or identifies all token transfers across a specified date range.

Setup guide

Set up Zetachain Explorer (ZetaChain Block Explorer API) 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 Zetachain Explorer (ZetaChain Block Explorer API) 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: "zetachain-explorer-zetachain-block-explorer-api-mcp-client",
  servers: {
    "zetachain-explorer-zetachain-block-explorer-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Zetachain Explorer (ZetaChain Block Explorer API) transactions"
);
console.log(result.text);

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Common questions about Zetachain Explorer (ZetaChain Block Explorer API) MCP in Mastra AI

The workflow first checks for the token using `get_token`. If found, it proceeds to check if an address is listed as a holder via `get_token_holders`. This two-step conditional process ensures high confidence in your data.

Yes. If a transaction lookup fails, the workflow can automatically retry calling `get_transaction` with exponential backoff before notifying your team that manual review is needed.

Use `get_transaction_internal` within a workflow. You can build logic that says: 'If an internal call is made, then analyze its logs.' This sequence handles the full lifecycle of a contract interaction.

Start by calling `list_blocks` to get the latest block hashes. Your workflow can then loop through these, running a specialized tool like `get_block_transactions` for each one until the desired time limit is reached.

This server deals with publicly recorded blockchain state, specifically token transfers and transaction hashes. This information is intended to be public on the ZetaChain network.

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