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

Q: How does LlamaIndex help me search complex blockchain data with Zetachain Explorer (ZetaChain Block Explorer API)?

LlamaIndex indexes the raw output from tools like getblock and gettransaction. You can then ask natural language questions, and it retrieves the correct chunk of API data to answer you, rather than just listing hashes.

Q: Can I index internal contract calls with Zetachain Explorer (ZetaChain Block Explorer API) using LlamaIndex?

Yes. When your client runs gettransactioninternal, the resulting data is captured and added to your searchable knowledge base. This makes auditing complex smart contracts much easier.

Q: How can I get a full picture of an address's activity with Zetachain Explorer (ZetaChain Block Explorer API) using LlamaIndex?

You run multiple queries—checking getaddresstransactions and getaddresstokenbalances. LlamaIndex combines the results, allowing you to query a unified narrative about that address's activity.

Q: What if I need to list many tokens or blocks using Zetachain Explorer (ZetaChain Block Explorer API) with LlamaIndex?

The output from listtokens or listblocks gets indexed. This means you can query about the existence of a specific token or block number, and it'll pull that record directly into your knowledge base.

Index your Zetachain data for RAG applications with LlamaIndex. Turn blockchain API results into a searchable knowledge base for your AI client.

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Connect Zetachain Explorer (ZetaChain Block Explorer API) MCP to LlamaIndex

Create your Vinkius account to connect Zetachain Explorer (ZetaChain Block Explorer API) to LlamaIndex 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 Zetachain Explorer (ZetaChain Block Explorer API) with LlamaIndex

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Indexing Transaction History

The output of `get_transaction` becomes part of your vector store, allowing semantic searching over past data. Instead of querying by hash, you can ask questions like, 'Show me all transactions involving this address last month.' LlamaIndex ingests the full transaction details—including internal calls found via `get_transaction_internal`—and indexes them for later retrieval.

Semantic Block and Address Queries

You can combine data from multiple sources into one searchable index. If you query an address, LlamaIndex uses the results of `get_address_transactions`, the token balances from `get_address_token_balances`, and the associated block details (`get_block`) to build a comprehensive answer. The AI client grounds its response in this live data, eliminating guesswork and hallucination.

Tracking Token Ownership Changes

All token movement is indexed. When you use `get_token_transfers` or check the history via `get_address_tokens`, LlamaIndex captures this change in ownership. You can then query, 'Which accounts held ETH between X and Y dates?' The data from `get_token_holders` populates your knowledge base for easy querying.

Setup guide

Set up Zetachain Explorer (ZetaChain Block Explorer API) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Zetachain Explorer (ZetaChain Block Explorer API) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Zetachain Explorer (ZetaChain Block Explorer API) tools.",
)
response = await agent.run("List recent Zetachain Explorer (ZetaChain Block Explorer API) data")

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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 ZetaChain Explorer. 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 Zetachain Explorer (ZetaChain Block Explorer API) MCP in LlamaIndex

LlamaIndex indexes the raw output from tools like `get_block` and `get_transaction`. You can then ask natural language questions, and it retrieves the correct chunk of API data to answer you, rather than just listing hashes.

Yes. When your client runs `get_transaction_internal`, the resulting data is captured and added to your searchable knowledge base. This makes auditing complex smart contracts much easier.

You run multiple queries—checking `get_address_transactions` and `get_address_token_balances`. LlamaIndex combines the results, allowing you to query a unified narrative about that address's activity.

The output from `list_tokens` or `list_blocks` gets indexed. This means you can query about the existence of a specific token or block number, and it'll pull that record directly into your knowledge base.

This server deals with publicly viewable blockchain records. The specific data types indexed include transaction hashes, wallet addresses, and token transfer logs.

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