Bring Referralhero
to Pydantic AI
Learn how to connect ReferralHero to Pydantic AI and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the ReferralHero MCP Server?
Connect your ReferralHero account to any AI agent and take full control of your viral growth orchestration and referral program management through natural conversation. ReferralHero provides a premier platform for building referral loops, and this integration allows you to retrieve subscriber metadata, monitor campaign leaderboards, and manage rewards directly from your chat interface.
What you can do
- Campaign & List Orchestration — List all managed referral campaigns and retrieve detailed metadata, including creating and updating subscriber records programmatically.
- Subscriber Lifecycle Management — Access and monitor individual subscriber profiles and retrieve detailed performance metadata including point balances directly from the AI interface.
- Leaderboard & Reward Intelligence — Access real-time campaign leaderboards and monitor reward eligibility via natural language to drive program engagement.
- Conversion & Referral Tracking — Track conversion events and attribute referrals to specific subscribers to ensure your growth loops are always synchronized.
- Operational Monitoring — Track system activity and manage transaction metadata using simple AI commands.
How it works
1. Subscribe to this server
2. Enter your ReferralHero API Token from your account settings
3. Start managing your referral campaigns from Claude, Cursor, or any MCP-compatible client
No more manual leaderboard exports or subscriber hunting. Your AI acts as a dedicated growth operations manager or referral coordinator.
Who is this for?
- Growth Marketers & Founders — quickly retrieve campaign summaries and monitor subscriber growth without switching apps.
- Marketing Operations Teams — automate the management of referral points and track reward distributions via natural conversation.
- Customer Success Teams — streamline the retrieval of subscriber metadata and monitor referral history directly within the chat.
Built-in capabilities (12)
Add points to a subscriber
Add a new subscriber to a campaign
Remove a subscriber from a campaign
Get campaign leaderboard
Get details for a specific campaign
Get campaign rewards
Get details for a specific subscriber
List all referral campaigns (lists)
List subscribers for a campaign
List recent transactions
Track a referral conversion event
Update an existing subscriber
Why Pydantic AI?
Pydantic AI validates every ReferralHero tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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 ReferralHero 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 ReferralHero connection logic from agent behavior for testable, maintainable code
ReferralHero in Pydantic AI
ReferralHero and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect ReferralHero 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 ReferralHero in Pydantic AI
The ReferralHero 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 12 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
ReferralHero for Pydantic AI
Every tool call from Pydantic AI to the ReferralHero 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 find the details and points for a specific subscriber by providing their ID?
Yes! Use the get_subscriber tool with the List UUID and Subscriber ID. Your agent will respond with complete metadata, including referral counts and current point balances in seconds.
How do I find my ReferralHero API Token?
Log in to your ReferralHero dashboard, navigate to Account > API, and you will find your unique secret token there.
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 ReferralHero MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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