How to Use the ChurchStamp MCP in Pydantic AI

Q: How does Pydantic AI help me manage ChurchStamp contacts reliably?

When your agent uses createcontact, Pydantic AI ensures the data you send matches the required format. When it uses listcontacts, it ensures the data you receive is what you expect. This prevents errors like misformatted addresses from breaking your automations.

Q: What's the setup process for ChurchStamp with Pydantic AI?

It's one line of code. You instantiate the MCPToolset class with your Vinkius endpoint URL and add it to your Pydantic AI Agent. There's no need to define the tool schemas yourself; they're discovered from the MCP Server.

Add type-safe access to your ChurchStamp campaigns and contacts with Pydantic AI's MCP integration.

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Connect ChurchStamp MCP to Pydantic AI

Create your Vinkius account to connect ChurchStamp 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 ChurchStamp with Pydantic AI

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Get Type-Safe ChurchStamp Operations

Pydantic AI turns every API call from this MCP Server into a validated, type-safe operation. When your agent uses `get_campaign` or `list_contacts`, the response is automatically parsed and checked against a Pydantic model. No more guessing what the API will return. If the ChurchStamp API ever returns data in an unexpected format, your agent will raise a `ValidationError` immediately. This prevents silent data corruption and makes debugging a hundred times easier. You know exactly where and why the data contract was broken.

Build Reliable Mailing Automations

Build agents that you can actually trust with your member data. An agent can use `create_contact` to add a new family to your directory or `create_campaign` to schedule the next newsletter, and you can be sure the inputs and outputs are correct. Because Pydantic AI is model-agnostic, you can use these validated tools with any LLM—OpenAI, Anthropic, a local model, whatever. You get consistent behavior for tools like `send_mail` no matter what brain is driving the agent.

Connect to the ChurchStamp MCP Server

This server gives your agent a complete, validated toolset for managing church mailings. It gets tools for listing designs (`list_designs`), checking campaign status (`get_campaign`), and managing your member list (`list_contacts`). Setup is simple. After installing `pydantic-ai-slim[mcp]`, you create an `MCPToolset` with your Vinkius server URL. Pass that toolset to your agent, and it's ready to go. The framework handles all the runtime validation for you.

Setup guide

Set up ChurchStamp 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": {
        "churchstamp-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about ChurchStamp MCP in Pydantic AI

It means every piece of data from the ChurchStamp API is validated against a strict schema. If your agent calls `get_campaign` and the API returns a malformed response, Pydantic AI will throw an error instead of letting your agent work with bad data.

Absolutely. Pydantic AI is model-agnostic, so you can connect the ChurchStamp MCP Server via the `MCPToolset` to an agent running on a local model, a private cloud model, or a public one like GPT-4 or Claude 3.

When your agent uses `create_contact`, Pydantic AI ensures the data you send matches the required format. When it uses `list_contacts`, it ensures the data you receive is what you expect. This prevents errors like misformatted addresses from breaking your automations.

It's one line of code. You instantiate the `MCPToolset` class with your Vinkius endpoint URL and add it to your Pydantic AI `Agent`. There's no need to define the tool schemas yourself; they're discovered from the MCP Server.

Pydantic AI operates as a validation layer within your own application's code. It processes member contact and campaign data in-memory, passing it through the Vinkius endpoint to the ChurchStamp API. Your data's privacy is maintained as it's not stored by Vinkius or the Pydantic AI library itself.

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