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

Q: How do I register the Blocknative (Ethereum Mempool API) MCP Server tools in Google ADK?

Use the McpToolset class with your Vinkius connection parameters to load the tools. Pass the resulting toolset directly to your LlmAgent instance in your Python code.

Give your Gemini agents live Blocknative mempool data using the Google ADK to optimize large-scale Ethereum operations.

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Connect Blocknative (Ethereum Mempool API) MCP to Google ADK

Create your Vinkius account to connect Blocknative (Ethereum Mempool API) to Google ADK 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 Google ADK

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Analyze Mempool Trends with Gemini and Google ADK

Enterprise agents built on the Google ADK can now feed live gas metrics directly into Vertex AI. The `get_gas_prices` tool lets your Gemini models retrieve real-time EIP-1559 base and priority fees on demand. Combining this live data with historical transaction records in BigQuery lets you build predictive models. Your agent reads the mempool, compares it to past trends, and decides the absolute best block for your transaction.

Long-Context Reasoning for Complex Gas Strategies

Gemini's massive token window allows your agent to analyze hours of gas fluctuations alongside live data. By calling `get_gas_prices` repeatedly, your agent builds a detailed timeline of mempool activity to find patterns. This MCP Server integration allows the agent to hold complex gas pricing tables in its memory. It can draft multi-step transaction strategies that adjust dynamically as network congestion rises or falls.

Granular Tool Control for Enterprise Safety

The Google ADK lets you restrict which tools your LLM can access. You can explicitly expose only `get_gas_prices` to your agent, ensuring it only reads market data and cannot execute unauthorized on-chain actions. This setup runs over secure HTTP or Stdio transports. It gives your agents a direct window via MCP into the Ethereum mempool without exposing any sensitive internal infrastructure.

Setup guide

Set up Blocknative (Ethereum Mempool API) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Blocknative (Ethereum Mempool API) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Blocknative (Ethereum Mempool API)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Blocknative (Ethereum Mempool API) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Blocknative (Ethereum Mempool API) MCP in Google ADK

Use the `McpToolset` class with your Vinkius connection parameters to load the tools. Pass the resulting toolset directly to your `LlmAgent` instance in your Python code.

Yes. Your agent can query historic gas tables stored in BigQuery and use the `get_gas_prices` tool to fetch live mempool metrics, combining both for smart decision-making.

Yes. The server integrates cleanly with Google ADK, allowing Gemini to process real-time gas price data alongside thousands of historical transaction logs in a single prompt.

You can connect using either Stdio or HTTP transport protocols, depending on how you host your Google ADK agent infrastructure.

Vinkius runs this MCP server inside an isolated sandbox. Your gas price queries are transient and never stored, ensuring your agent's search patterns remain completely confidential.

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