How do I get my AntChain Access Key and Secret Key?

Log in to the AntChain BaaS console, navigate to the API Management or Developer Center section, and create a new API credential pair. You'll receive an Access Key (public identifier) and a Secret Key (used for HMAC-SHA256 signature generation). The Secret Key is shown only once — save it immediately. These credentials authenticate all your API requests.

What's the difference between querying a block and querying a transaction?

A block query returns information about the container itself — block height, hash, timestamp, transaction count, and the previous block hash. A transaction query returns details about a specific operation within a block — sender/receiver addresses, gas used, execution status, return values, and whether the transaction succeeded or reverted. Use blocks to explore the chain structure, and transactions to verify individual operations.

Can I deploy smart contracts through this MCP server?

Yes! Use the `deploy_contract` tool to upload and deploy compiled smart contract bytecode to your AntChain network. You'll need the contract bytecode (in hex format), a name for the contract, and optionally the ABI for future interactions. After deployment, you can invoke contract methods using the `invoke_contract` tool. Make sure your account has sufficient permissions and balance for deployment.

AntChain MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: AntChain
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect AntChain through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to AntChain "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in AntChain?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About AntChain MCP Server

Connect your AntChain (蚂蚁链) BaaS platform account to any AI agent and gain complete visibility and control over your enterprise blockchain operations through natural conversation. AntChain is Alibaba Group's blockchain-as-a-service platform, designed for consortium chains, enterprise smart contracts, and secure decentralized applications.

Pydantic AI validates every AntChain tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Block Exploration — Query detailed information about any block by height or hash, including transaction counts and timestamps
Transaction Tracking — Inspect individual transactions by hash or ID, verifying status, gas consumption, and execution results
Smart Contract Management — Deploy new contracts, invoke contract methods, and query contract metadata and ABIs
Account Inspection — Check account balances, nonce values, and metadata for any wallet address on the chain
Network Monitoring — View network topology, node status, consensus state, and chain health metrics
Chain Discovery — List all blockchain networks available to your organization with their configurations
Recent Activity — Monitor the latest transactions and network activity in real-time

The AntChain MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect AntChain to Pydantic AI via MCP

Follow these steps to integrate the AntChain MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from AntChain with type-safe schemas

Why Use Pydantic AI with the AntChain MCP Server

Pydantic AI provides unique advantages when paired with AntChain through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your AntChain integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your AntChain connection logic from agent behavior for testable, maintainable code

AntChain + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the AntChain MCP Server delivers measurable value.

Type-safe data pipelines: query AntChain with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple AntChain tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query AntChain and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock AntChain responses and write comprehensive agent tests

AntChain MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect AntChain to Pydantic AI via MCP:

deploy_contract

Requires the contract bytecode (compiled bytecode in hex format) and optionally the ABI (Application Binary Interface) for interaction. Returns the deployed contract address and deployment transaction details. The contract will be available under the specified name. Deploy a smart contract on AntChain

get_chain_list

Returns chain IDs, names, creation dates, status, and basic configuration. Use this to discover which blockchains you have access to before performing operations. List all available blockchain networks in your AntChain account

invoke_contract

Provide the contract name, method name, and any required arguments. Returns the execution result including return values, gas consumption, and transaction status. Use this to interact with deployed contracts. Invoke a smart contract method on AntChain

query_account

Use this to inspect account state and activity. Query account information on AntChain

query_account_balance

Returns the available balance and any locked/pending amounts. Useful for checking if an account has sufficient funds for transactions or contract interactions. Query account balance on AntChain

query_block

Returns block metadata including timestamp, transaction count, hash, and previous block reference. Use either blockHeight or blockHash to identify the block. Query block details from an AntChain blockchain

query_contract

Useful for inspecting contract configuration before invocation. Query smart contract information on AntChain

query_latest_transactions

Useful for monitoring network activity, auditing recent transactions, or getting a snapshot of current blockchain operations. Returns a list of recent transactions with their status and metadata. Query the latest transactions on an AntChain blockchain

query_network_info

Useful for monitoring blockchain infrastructure health. Query blockchain network information on AntChain

query_transaction

Returns transaction status, sender, receiver, gas used, block inclusion, and execution result. Useful for verifying transaction finality and inspecting transaction details. Query a transaction on AntChain

Example Prompts for AntChain in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with AntChain immediately.

"Show me the latest 5 transactions on my default AntChain network."

"What's the balance of account 0x742d35Cc6634C0532925a3b844Bc9e7595e0bFa8?"

"Invoke the 'transfer' method on contract 'TokenContract' with args {"to": "0x123...", "amount": 100}."

Troubleshooting AntChain MCP Server with Pydantic AI

Common issues when connecting AntChain to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

AntChain + Pydantic AI FAQ

Common questions about integrating AntChain MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your AntChain MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.