How to Use the Vouchery.io MCP in Pydantic AI

Q: Can I delete campaigns using Vouchery.io and Pydantic AI?

Yes, the deletecampaign tool is available. The type safety ensures that when you call it, all necessary parameters are correctly provided to the underlying server.

Q: How do I list redemptions using Vouchery.io and Pydantic AI?

You call listredemptions. The returned data structure will be validated against your model, so you never have to worry about unexpected fields.

Q: Is getting voucher details reliable with Vouchery.io and Pydantic AI?

It's highly reliable. When using getvoucher, the response is strictly validated against your defined schema, guaranteeing data correctness every time you run it.

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Connect Vouchery.io MCP to Pydantic AI

Create your Vinkius account to connect Vouchery.io 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 Vouchery.io with Pydantic AI

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Manage Vouchery Campaigns

Your agent can list all marketing campaigns with `list_campaigns`. Because of Pydantic validation, you know exactly what fields are returned for every campaign. When starting a new promotion, call `create_campaign`. The runtime type checking guarantees the name and type inputs are correct before execution.

Process Voucher Claims

The agent calls `redeem_voucher` to process claims. If Vouchery.io returns malformed data, Pydantic fails loudly, telling you exactly what went wrong. You can check a specific code using `get_voucher`, and the resulting object is guaranteed to match your expected Python structure.

Track Customer Accounts

To see all users, use `list_customers`. The Pydantic framework validates that every customer record received has required fields like ID and name. You can maintain records by calling `create_customer`, ensuring the data you input adheres to strict type definitions.

Setup guide

Set up Vouchery.io 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": {
        "voucheryio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Vouchery.io transactions")
print(result.output)

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Common questions about Vouchery.io MCP in Pydantic AI

It wraps the MCP calls into Python objects that must adhere to defined Pydantic schemas. This means your agent gets clean, predictable data every single time.

Yes, the `delete_campaign` tool is available. The type safety ensures that when you call it, all necessary parameters are correctly provided to the underlying server.

This MCP Server focuses on structured data types for customer accounts, campaign definitions, and redemption logs. Accuracy is paramount here.

You call `list_redemptions`. The returned data structure will be validated against your model, so you never have to worry about unexpected fields.

It's highly reliable. When using `get_voucher`, the response is strictly validated against your defined schema, guaranteeing data correctness every time you run it.

Use it with your favorite AI tools

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