How to Use the BlockPi (Distributed RPC Network) MCP in Pydantic AI

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Connect BlockPi (Distributed RPC Network) MCP to Pydantic AI

Create your Vinkius account to connect BlockPi (Distributed RPC Network) to Pydantic AI 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 Pydantic AI

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Validate raw blockchain responses with Pydantic AI

The `rpc_call` tool delivers structured chain data directly to your agent, which Pydantic AI validates at runtime. If a node returns unexpected formats, your system catches it immediately before it corrupts your app state. This type safety is crucial when dealing with EVM hex outputs and block headers. This MCP Server ensures that your agent only works with verified, structurally sound blockchain responses.

Enforce schemas on RU metrics

The `get_ru_balance` and `get_ru_consumed` tools return precise integer values for your remaining Request Units. Pydantic AI validates these numeric fields so your agent never makes decisions based on stringified or malformed data. You can define strict schemas for your monitoring loops. If the API response deviates from the expected model, the agent fails loudly instead of silently ignoring the issue.

Monitor wallet balances with strict type guarantees

The `get_wallet_balance` and `get_package_expiration` tools provide your agent with exact USD values and expiration timestamps. Your agent can safely run mathematical operations on these validated floats. By avoiding silent validation failures, you prevent your agents from miscalculating your remaining budget. It makes your production automated billing workflows incredibly reliable.

Setup guide

Set up BlockPi (Distributed RPC Network) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "blockpi-distributed-rpc-network-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to BlockPi (Distributed RPC Network) tools.",
)

result = await agent.run("List recent BlockPi (Distributed RPC Network) transactions")
print(result.output)

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Common questions about BlockPi (Distributed RPC Network) MCP in Pydantic AI

Use the MCPToolset class initialized with your Vinkius HTTP endpoint. Pass this toolset into your Agent's toolsets list.

The framework will raise a validation error immediately. This stops the agent from executing further tasks with corrupt RPC data.

Yes, because Pydantic AI is model-agnostic. You can pair this server with local models or commercial APIs like Anthropic.

The MCPServerHTTP class is deprecated in modern versions of the framework. The unified MCP toolset class provides a cleaner, more stable connection to your hosted servers.

All requests to fetch RU balances or execute blockchain transactions are encrypted in transit via HTTPS. Vinkius manages the authentication tokens securely, meaning your raw API keys never leak to the client side.

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