Copperx MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Copperx through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Copperx "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Copperx?"
)
print(result.data)
asyncio.run(main())
* 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 Copperx MCP Server
Integrate Copperx, the API-first crypto payment processor, directly into your AI workflow. Automate your web3 billing, manage customer subscriptions, and track payouts using natural language.
Pydantic AI validates every Copperx tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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
- Payment Links — Create and manage checkout links for products or services instantly.
- Subscription Management — List and monitor active recurring billing cycles.
- Invoicing — Generate and track crypto invoices for your global customers.
- Wallet Insights — Check your account balances across multiple chains and currencies.
The Copperx 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 Copperx to Pydantic AI via MCP
Follow these steps to integrate the Copperx 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 Copperx with type-safe schemas
Why Use Pydantic AI with the Copperx MCP Server
Pydantic AI provides unique advantages when paired with Copperx 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 Copperx integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Copperx connection logic from agent behavior for testable, maintainable code
Copperx + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Copperx MCP Server delivers measurable value.
Type-safe data pipelines: query Copperx with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Copperx tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Copperx and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Copperx responses and write comprehensive agent tests
Copperx MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Copperx to Pydantic AI via MCP:
create_customer
Creates a new customer record with identity properties (email, name) for future payment associations. Register a new customer in Copperx
create_payment_link
Resolves product identity and pricing configuration to generate a unique payment URL. Create a new payment link for customers to pay
get_payment_details
Resolves granular transaction data, including blockchain tx hashes, fee breakdowns, and customer linkages. Get details for a specific payment intent
get_wallet_balance
Resolves real-time wallet balances across various supported cryptocurrencies and networks. Check current crypto wallet balances in Copperx
list_customers
Resolves customer identity properties such as unique identifiers, email addresses, and registered names. List all customers registered in Copperx
list_invoices
Resolves billing document properties including invoice numbers, totals, and payment status links. List all invoices generated
list_payment_links
Resolves link metadata including checkout URLs, pricing data, and usage statistics. List all payment links created
list_payments
Resolves payment identity properties including transaction IDs, amounts, currencies, and processing status across the crypto-payment boundary. List all payment intents in Copperx
list_payouts
Resolves disbursement data including payout IDs, destination wallet addresses, and settlement status. List all payouts processed
list_subscriptions
Resolves subscription properties including plan IDs, billing cycles, and current subscription state. List all active and past subscriptions
Example Prompts for Copperx in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Copperx immediately.
"Create a crypto payment link for 'Consulting Service' worth 100 USDC."
"Check my current account balances across all crypto wallets."
"List all active subscriptions and their monthly revenue."
Troubleshooting Copperx MCP Server with Pydantic AI
Common issues when connecting Copperx to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCopperx + Pydantic AI FAQ
Common questions about integrating Copperx MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Copperx with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Copperx to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.