How to Use the Blastscan (Blast Network Explorer) MCP in LlamaIndex

Q: Does Blastscan (Blast Network Explorer) work with LlamaIndex RAG pipelines?

Yes. Your LlamaIndex RAG pipeline can call getlogs or geterc20transfers to fetch fresh transaction data, index it instantly, and use it to answer user questions about recent Blast activity.

Q: Can I limit which Blastscan (Blast Network Explorer) tools my LlamaIndex agent can access?

Yes, you can use the allowedtools filter when setting up McpToolSpec. This lets you restrict the agent to read-only tools like getetherbalance while blocking gas estimation tools if they are not needed.

Q: How do I handle token balances in a LlamaIndex query engine?

You pass geterc20tokenbalance as a tool to your FunctionAgent. When a user asks about a token balance, the agent calls the tool, gets the raw balance, and uses it to construct a response.

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Connect Blastscan (Blast Network Explorer) MCP to LlamaIndex

Create your Vinkius account to connect Blastscan (Blast Network Explorer) 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 Blastscan (Blast Network Explorer) with LlamaIndex

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Turn live Blast contract data into LlamaIndex RAG sources

Stop relying on outdated static documents to analyze smart contracts. This MCP server lets your LlamaIndex agent fetch the latest code using `get_contract_source_code` and index it directly into your vector database. Your agent can then perform semantic searches over live Solidity code rather than guessing based on old GitHub repos. By combining `get_contract_abi` with your index, the agent answers highly technical questions about contract methods with zero hallucinations. It references actual, verified on-chain code instead of generic EVM patterns.

Index Blast transaction histories for semantic search

Tracking down complex transaction patterns manually is slow. Use `get_normal_transactions` and `get_internal_transactions` to pull raw transaction histories and feed them straight into your LlamaIndex document store. Your agent can then query past wallet behaviors using natural language. You can ask questions like 'find all transactions that interacted with the liquidity pool last Tuesday' and let LlamaIndex search through the indexed payload. The agent parses the logs returned by `get_logs` to reconstruct exact on-chain events.

Query real-time Blast balances using this MCP Server

Keep your financial indexes accurate with live balance checks. Your LlamaIndex agent can run `get_ether_balance_multi` or `get_erc20_token_balance` to pull current holdings before answering user queries. This ensures your financial RAG pipeline never quotes stale data. The tool output is treated as a dynamic document resource. This means your agent can cross-reference the total supply from `get_erc20_token_supply` with individual balances to calculate real-time ownership percentages on the fly.

Setup guide

Set up Blastscan (Blast Network Explorer) 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 Blastscan (Blast Network Explorer) 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 Blastscan (Blast Network Explorer) tools.",
)
response = await agent.run("List recent Blastscan (Blast Network Explorer) data")

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Common questions about Blastscan (Blast Network Explorer) MCP in LlamaIndex

Use llama-index-tools-mcp to load the Blastscan tools. You can convert the tools into indexable documents by running the tool commands like `get_contract_source_code` and passing the text outputs directly to your vector store indexer.

Yes. Your LlamaIndex RAG pipeline can call `get_logs` or `get_erc20_transfers` to fetch fresh transaction data, index it instantly, and use it to answer user questions about recent Blast activity.

Yes, you can use the allowed_tools filter when setting up McpToolSpec. This lets you restrict the agent to read-only tools like `get_ether_balance` while blocking gas estimation tools if they are not needed.

You pass `get_erc20_token_balance` as a tool to your FunctionAgent. When a user asks about a token balance, the agent calls the tool, gets the raw balance, and uses it to construct a response.

The server processes all queries for balances and transaction hashes inside a secure, ephemeral V8 container on Vinkius. No on-chain read operations or ABI fetches are stored or cached, keeping your query history private.

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