How to Use the Blockscout MCP in Google ADK

Q: How do I link Blockscout to my Google ADK agent?

You instantiate the McpToolset with the Vinkius endpoint. Once initialized, the agent registers all available tools automatically for your workflows.

Q: Does Blockscout support the long-context features in Google ADK?

Yes, you can pull large sets of transaction history via getaccounttransactions and feed them into the model's context. Gemini handles the analysis of the returned data.

Connect Google ADK agents to live Ethereum data for high-context analysis on Google Cloud.

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Connect Blockscout MCP to Google ADK

Create your Vinkius account to connect Blockscout 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 Blockscout with Google ADK

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Analyze chain events in Google ADK

Use `get_logs` to stream event data into your Gemini-powered agents. This allows for deep analysis of historical contract interactions across large datasets. Your agent processes these logs to summarize complex protocol behavior. It works perfectly with long-context models that need to parse thousands of events at once.

Track token flows with Google ADK

Query `list_token_balances` to see exactly what an address holds. You can build agents that audit portfolios or track treasury movements in real time. This tool simplifies the process of aggregating assets across multiple standard tokens. It turns messy blockchain data into an object your agent can reason about immediately.

Retrieve block data for Google ADK

Call `get_block` to pull header details, gas usage, and timestamps for any specific block. This provides the necessary context for agents analyzing network performance. Your agent uses this data to calculate network health or verify specific transaction inclusion. It keeps your pipeline grounded in verifiable on-chain facts.

Setup guide

Set up Blockscout 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 Blockscout 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="Blockscout_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Blockscout tools via MCP.",
    tools=mcp_tools,
)

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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 Blockscout. 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.

Why Choose Vinkius

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Common questions about Blockscout MCP in Google ADK

You instantiate the `McpToolset` with the Vinkius endpoint. Once initialized, the agent registers all available tools automatically for your workflows.

Yes, you can pull large sets of transaction history via `get_account_transactions` and feed them into the model's context. Gemini handles the analysis of the returned data.

It is. You can host the connection within your cloud environment and expose the tools to your managed agent instances.

The server requires a single endpoint token provided by Vinkius. This keeps your connection isolated and authenticated without hardcoded secrets.

The server only touches public blockchain data and discards it after the request finishes. No logs are cached on the server side.

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