ReferralCandy MCP Server for Pydantic AIGive Pydantic AI instant access to 16 tools to Check Referralcandy Status, Get Campaign, Get Referral, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect ReferralCandy through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The ReferralCandy app connector for Pydantic AI is a standout in the Marketing Automation category — giving your AI agent 16 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 ReferralCandy "
"(16 tools)."
),
)
result = await agent.run(
"What tools are available in ReferralCandy?"
)
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 ReferralCandy MCP Server
Give your AI agent full programmatic control over your ReferralCandy ecosystem. With 16 tools tailored for referral marketing, your agent can instantly track referrals by period, register attributed purchases, identify top advocates, monitor pending rewards, manage campaigns, and send referral invitations directly from your natural language workspace.
Pydantic AI validates every ReferralCandy tool response against typed schemas, catching data inconsistencies at build time. Connect 16 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
- List and filter referrals by period
- Register purchases to trigger rewards
- Identify and manage top-performing advocates
- Monitor pending referral payouts
- Configure campaigns and send invites
- Access overall program statistics
Who is it for?
Designed for marketing teams, e-commerce operators, and growth hackers who need instant, conversational access to affiliate and referral performance metrics.The ReferralCandy MCP Server exposes 16 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.
All 16 ReferralCandy tools available for Pydantic AI
When Pydantic AI connects to ReferralCandy through Vinkius, your AI agent gets direct access to every tool listed below — spanning referral-marketing, affiliates, loyalty, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Get campaign details
Get referral details
Get advocate profile
Get program stats
Get top advocates
List campaigns
List sent invites
List pending rewards
List referred purchases
List all referrals
List referrals by period
List all advocates
List all rewards
Register a purchase
Send a referral invite
Connect ReferralCandy to Pydantic AI via MCP
Follow these steps to wire ReferralCandy into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the ReferralCandy MCP Server
Pydantic AI provides unique advantages when paired with ReferralCandy 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 ReferralCandy integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your ReferralCandy connection logic from agent behavior for testable, maintainable code
ReferralCandy + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the ReferralCandy MCP Server delivers measurable value.
Type-safe data pipelines: query ReferralCandy with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple ReferralCandy tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query ReferralCandy and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock ReferralCandy responses and write comprehensive agent tests
Example Prompts for ReferralCandy in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with ReferralCandy immediately.
"Can you find the top referrers in my ReferralCandy program for the last month?"
"Register a purchase of $150.00 for order #90210 by customer@example.com."
"List all pending referral rewards that need to be processed this week."
Troubleshooting ReferralCandy MCP Server with Pydantic AI
Common issues when connecting ReferralCandy to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiReferralCandy + Pydantic AI FAQ
Common questions about integrating ReferralCandy 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.