Referrizer MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Create Contact, Get Campaign, Get Contact Details, and more

Name: Referrizer
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Referrizer MCP Server for Pydantic AI is a standout in the Marketing Automation category — giving your AI agent 11 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 Referrizer "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Referrizer?"
    )
    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 Referrizer MCP Server

Connect your Referrizer account to any AI agent and simplify your referral marketing, customer loyalty, and retention workflows through natural conversation.

Pydantic AI validates every Referrizer tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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

Contact Management — List all customers and contacts, retrieve detailed profile metadata, and monitor loyalty points and status
Referral Tracking — Access a history of successful and pending customer referrals to understand your word-of-mouth growth
Campaign Control — Query past and active marketing automation campaigns to monitor your outreach performance
Loyalty Rewards — List available rewards and incentives to choose the right context for each interaction
Direct Enrollment — Register new contacts and customers programmatically directly from your agent

The Referrizer MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Referrizer tools available for Pydantic AI

When Pydantic AI connects to Referrizer through Vinkius, your AI agent gets direct access to every tool listed below — spanning referral-marketing, loyalty-programs, customer-retention, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Update a contact profile

Connect Referrizer to Pydantic AI via MCP

Follow these steps to wire Referrizer into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 11 tools from Referrizer with type-safe schemas

Why Use Pydantic AI with the Referrizer MCP Server

Pydantic AI provides unique advantages when paired with Referrizer 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 Referrizer integration code

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

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

Referrizer + Pydantic AI Use Cases

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

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

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

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

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

Example Prompts for Referrizer in Pydantic AI

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

"List all active contacts in Referrizer."

"Show me the ROI analysis for all active loyalty and referral campaigns."

"Create a new contact and enroll them in the Birthday Rewards campaign."

Troubleshooting Referrizer MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Referrizer + Pydantic AI FAQ

Common questions about integrating Referrizer 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 Referrizer MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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