Bring Referral Marketing
to Pydantic AI
Learn how to connect ReferralCandy to Pydantic AI and start using 16 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the 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.
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
How it works
1. Subscribe to this server 2. Enter your ReferralCandy API Keys (found in your developer settings) 3. Let your AI agents start managing your referral operations via VinkiusWho is it for?
Designed for marketing teams, e-commerce operators, and growth hackers who need instant, conversational access to affiliate and referral performance metrics.Built-in capabilities (16)
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
Why Pydantic AI?
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.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your ReferralCandy integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your ReferralCandy connection logic from agent behavior for testable, maintainable code
ReferralCandy in Pydantic AI
ReferralCandy and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect ReferralCandy to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for ReferralCandy in Pydantic AI
The ReferralCandy 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. All 16 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
ReferralCandy for Pydantic AI
Every tool call from Pydantic AI to the ReferralCandy MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can my AI automatically register a new purchase to trigger a referral reward?
Yes! Use the register_purchase tool providing the buyer's email, order amount, and order ID. Your agent will send this data to ReferralCandy, triggering the referral attribution and payout flow instantly.
How do I easily find out who my best performing advocates are?
Simply ask the agent to run the get_top_referrers action. It will compile your highest-performing ambassadors ranked by total successful referrals and the total revenue they generated for your store.
Can I check if a specific customer has any pending referral rewards?
Absolutely. By using the list_pending_rewards tool and filtering by the customer's email, your agent can instantly fetch their reward status and payout timeline without you needing to open the dashboard.
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 ReferralCandy MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai