How to Use the Blockdaemon (Blockchain Infrastructure) MCP in Pydantic AI

Q: How do I configure the Blockdaemon (Blockchain Infrastructure) toolset in Pydantic AI?

Use the unified MCPToolset class initialized with your Vinkius server URL. Pass this toolset inside the toolsets list when instantiating your Pydantic AI Agent.

Q: Is the older MCPServerHTTP class still supported for this integration?

No, MCPServerHTTP is deprecated. You should use the unified MCPToolset approach to connect your Pydantic AI agents to the Blockdaemon server.

Run type-safe blockchain operations with Pydantic AI to validate Blockdaemon ledger data at runtime.

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Connect Blockdaemon (Blockchain Infrastructure) MCP to Pydantic AI

Create your Vinkius account to connect Blockdaemon (Blockchain Infrastructure) 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 Blockdaemon (Blockchain Infrastructure) with Pydantic AI

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Perplexity

Validate Blockdaemon (Blockchain Infrastructure) data

Blockchain data is complex and prone to structural changes. Pydantic AI ensures that every payload returned by `get_financial_report` or `get_utxos` conforms exactly to your defined Python schemas before your agent even processes it. If the blockchain API returns unexpected null fields or altered types, the framework fails loudly. This prevents silent corruption in your database and guarantees your financial reports are built on clean, validated data.

Query this MCP Server using any LLM provider

Pydantic AI is not locked into one model. You can use this MCP Server to fetch transaction lists via `list_transactions` using OpenAI, Anthropic, or local models like Llama, all while keeping the same validation logic. This flexibility allows you to swap models as pricing or performance needs change. Your code remains identical; the agent simply calls the blockchain tools and validates the incoming payloads against your Pydantic schemas.

Parse live block data into clean Python objects

Track network progress without dealing with raw JSON parsing. Your agent can call `list_blocks` to get the latest block identifiers, converting the raw network responses into typed Python models automatically. To set this up, initialize the MCP toolset with your Vinkius HTTP endpoint and pass it to your Agent. The framework handles the SSE or HTTP transport details, giving you a clean interface for blockchain monitoring.

Setup guide

Set up Blockdaemon (Blockchain Infrastructure) 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": {
        "blockdaemon-blockchain-infrastructure-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Blockdaemon (Blockchain Infrastructure) tools.",
)

result = await agent.run("List recent Blockdaemon (Blockchain Infrastructure) transactions")
print(result.output)

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Common questions about Blockdaemon (Blockchain Infrastructure) MCP in Pydantic AI

The framework intercepts the raw JSON responses from tools like `get_financial_report` and runs them through Pydantic models. If the ledger data doesn't match the expected schema, it raises a validation error immediately.

Use the unified `MCPToolset` class initialized with your Vinkius server URL. Pass this toolset inside the `toolsets` list when instantiating your Pydantic AI Agent.

Yes. Pydantic AI is model-agnostic, meaning you can hook up local models or proprietary APIs to query UTXOs and blocks while maintaining strict runtime validation.

No, `MCPServerHTTP` is deprecated. You should use the unified `MCPToolset` approach to connect your Pydantic AI agents to the Blockdaemon server.

All requests to fetch UTXOs or transaction lists are routed through Vinkius's secure, ephemeral V8 isolates. Your wallet addresses and financial queries are never cached or stored, keeping your on-chain analysis private and secure.

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