How to Use the Blocknative (Ethereum Mempool API) MCP in LangChain

Build gas-aware transaction chains in LangChain by plugging directly into the Blocknative mempool feed.

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Connect Blocknative (Ethereum Mempool API) MCP to LangChain

Create your Vinkius account to connect Blocknative (Ethereum Mempool API) to LangChain 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 Blocknative (Ethereum Mempool API) with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Real-time gas price logic for LangChain

Feed live mempool data into your agentic chains. Using `get_gas_prices`, your chain makes informed decisions on transaction timing based on current congestion. This prevents your agent from submitting stuck transactions during spikes. It links the Blocknative mempool state directly to your next execution step.

Automated pipeline triggers

Chain the output of your gas estimation directly into your signing logic. Each step in your LangChain sequence reacts to the specific cost data returned by `get_gas_prices`. Your agents now act on current market conditions instead of stale estimates. The flow stays tight and reactive without manual intervention.

Full observability for Ethereum transactions

Trace every gas decision within your LangSmith dashboard. You see exactly how the agent interpreted the Blocknative `get_gas_prices` output for every step in the chain. Debugging failed transactions becomes simple when you track the exact gas price the agent saw at the moment of decision. This visibility keeps your production pipelines transparent.

Setup guide

Set up Blocknative (Ethereum Mempool API) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Blocknative (Ethereum Mempool API) tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "blocknative-ethereum-mempool-api-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Blocknative (Ethereum Mempool API) transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Blocknative (Ethereum Mempool API) MCP in LangChain

You install the MCP adapters and point your client to the Vinkius endpoint. This lets your agents pull real-time gas data into their decision-making process.

Yes. Your agents use the gas data to decide if they should proceed with a transaction or wait for a price drop.

The server remains stateless, but your LangChain agent can store the returned gas prices in its message history for context.

Pass a tools list to the agent constructor. You can restrict it to only use specific functions from the server.

This server only fetches public mempool gas estimates. It does not touch your private keys or sensitive user wallet data.

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