Bring Loyalty Programs
to Pydantic AI
Learn how to connect Zinrelo to Pydantic AI and start using 9 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the Zinrelo MCP Server?
Connect your Zinrelo account to any AI agent to automate your loyalty and rewards operations. This MCP server enables your agent to interact with loyalty members, award points for activities or purchases, and manage reward redemptions directly from natural language.
What you can do
- Member Management — Enroll new customers and retrieve detailed loyalty profiles, including tier status and point balances
- Points Automation — Award points for custom activities or purchase transactions instantly
- Reward Processing — Redeem points for rewards and manage manual point deductions when necessary
- Activity Auditing — List comprehensive transaction histories for any loyalty member to track earnings and usage
- Program Oversight — Access high-level loyalty settings and account configuration details
How it works
1. Subscribe to this server
2. Enter your Zinrelo Partner ID and API Key
3. Start managing your loyalty program from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Marketing Managers — Monitor loyalty member growth and award points for special campaigns via natural language
- Customer Support — Quickly check a customer's point balance or transaction history during interactions
- E-commerce Owners — Automate the enrollment of new members and tracking of reward activities
Built-in capabilities (9)
Award points for a custom activity
Award points for a purchase
Manually deduct points from a user
Enroll or update a loyalty member
Get account loyalty settings
Get details for a specific loyalty member
List all loyalty program members
List transaction history for a member
g., coupon). Redeem points for a reward
Why Pydantic AI?
Pydantic AI validates every Zinrelo tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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 Zinrelo 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 Zinrelo connection logic from agent behavior for testable, maintainable code
Zinrelo in Pydantic AI
Zinrelo and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Zinrelo 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 Zinrelo in Pydantic AI
The Zinrelo 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 9 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
Zinrelo for Pydantic AI
Every tool call from Pydantic AI to the Zinrelo MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I award points for a specific activity?
Use the award_points_activity tool with the member's email and the specific activity_id defined in your Zinrelo dashboard.
Can I see a history of point redemptions for a user?
Yes, the list_member_transactions tool retrieves a complete history of all point earnings and redemptions for a target member.
Is it possible to manually deduct points?
Absolutely. Use the deduct_points tool to remove a specific amount of points from a user's loyalty balance.
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 Zinrelo MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai