How to Use the BlockPi (Distributed RPC Network) MCP in Google ADK

Connect Gemini's million-token context to decentralized nodes using Google ADK.

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Connect BlockPi (Distributed RPC Network) MCP to Google ADK

Create your Vinkius account to connect BlockPi (Distributed RPC Network) 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 BlockPi (Distributed RPC Network) with Google ADK

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Query distributed nodes using Google ADK

The `rpc_call` tool connects Gemini's long-context reasoning directly to live blockchain data. Your agent can pull thousands of blocks and analyze smart contract states in a single prompt. Integrating this MCP Server into your Google Cloud setup lets you feed real-time chain data into Vertex AI pipelines. It eliminates the need to build custom Web3 middleware for your enterprise agents.

Feed node consumption data directly into BigQuery

The `get_ru_consumed` and `get_ru_balance` tools let your Google ADK agent track node costs on the fly. You can write a workflow that queries these endpoints and dumps the metrics directly into a database. This data helps you optimize your resource allocations. Your agent can automatically alert your engineering team on Google Chat when your Request Units drop below a set threshold.

Monitor active package lifespans within Gemini workflows

The `get_package_expiration` and `get_wallet_balance` tools give your LLM agent full visibility into your BlockPi account health. The agent can check when packages expire and cross-reference that with your USD balance. Having this data in the context window allows Gemini to make smart decisions about resource renewals. It keeps your enterprise blockchain pipelines running without manual tracking.

Setup guide

Set up BlockPi (Distributed RPC Network) 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 BlockPi (Distributed RPC Network) 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="BlockPi (Distributed RPC Network)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BlockPi (Distributed RPC Network) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about BlockPi (Distributed RPC Network) MCP in Google ADK

Install google-adk and initialize McpToolset with your Vinkius HTTP URL. Pass that toolset into your LlmAgent instance to expose the tools.

Absolutely, you can pass multiple toolsets to your LlmAgent. This allows your agent to fetch blockchain data via rpc_call and immediately write it to BigQuery.

Yes, the ADK supports both Stdio and Streamable HTTP transports. For hosted Vinkius servers, you will use the Streamable HTTP parameters.

Gemini's native tool-calling mechanism parses the structured JSON outputs from the RPC endpoints. The model extracts the raw hex data or balance metrics automatically.

Your raw JSON-RPC queries and RU consumption metrics are processed in memory. This MCP server runs in an isolated V8 sandbox, ensuring your proprietary transaction details remain private.

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