How to Use the Arbiscan (Arbitrum Explorer) MCP in Pydantic AI

Validate all Arbitrum blockchain interactions using Pydantic AI models.

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Connect Arbiscan (Arbitrum Explorer) MCP to Pydantic AI

Create your Vinkius account to connect Arbiscan (Arbitrum Explorer) 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 Arbiscan (Arbitrum Explorer) with Pydantic AI

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Type-safe Arbitrum data for Pydantic AI

Fetch balance and price data with guaranteed schema validation. When you call `get_balance` or `get_eth_price`, Pydantic AI checks that the response matches your expected structure. If the network returns malformed data, your agent stops immediately. This prevents bad state from propagating through your logic.

Contract verification in Pydantic AI

Inspect smart contracts with the safety of runtime type checking. Use `get_source_code` and `get_abi` to pull details while ensuring the output satisfies your Pydantic models. Your agents won't hallucinate fields because the framework rejects any response that doesn't fit the schema. It makes working with complex contract data predictable.

Query transaction lists with Pydantic AI

Track address activity while maintaining strict data integrity. The `get_tx_list` and `get_token_tx` tools return data that is instantly validated against your definitions. This approach removes the risk of silent data corruption. Your agent knows exactly what it received before it makes a decision.

Setup guide

Set up Arbiscan (Arbitrum Explorer) 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": {
        "arbiscan-arbitrum-explorer-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Arbiscan (Arbitrum Explorer) transactions")
print(result.output)

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Common questions about Arbiscan (Arbitrum Explorer) MCP in Pydantic AI

Initialize an MCPToolset with the Vinkius server URL and pass it to your Agent definition. Pydantic AI then validates every tool response at runtime.

It does. Every tool output is checked against your Pydantic model definitions. If the data structure deviates, the agent raises a validation error.

Yes. The framework supports both Streamable HTTP and SSE transports. You define your connection once and the agent handles the rest.

The type-safe nature of the framework ensures that your agent only operates on data that matches your requirements. It eliminates guesswork.

The server retrieves public blockchain transaction lists, event logs, and contract codes. Security is maintained by treating all external data as untrusted until validated by your Pydantic models.

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