Bring Gift Cards
to Pydantic AI
Learn how to connect Tango 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 Tango MCP Server?
Connect your Tango (formerly Tango Card) reward platform account to any AI agent and simplify how you distribute digital gift cards, manage customers, and monitor funding accounts through natural conversation.
What you can do
- Catalog Discovery — Browse the full global catalog of brands, including gift cards, prepaid cards, and non-profit donations.
- Reward Distribution — Place and automate orders for digital rewards delivered via email instantly.
- Customer & Account Management — List, create, and manage customer groups and their associated funding accounts.
- Financial Oversight — Check real-time account balances, list funding sources, and retrieve current exchange rates.
- Order Tracking — Monitor your reward history and fetch detailed status and credentials for specific order IDs.
- Scalable Rewards — Coordinate bulk payouts and loyalty incentives directly from Claude, Cursor, or any MCP client.
How it works
1. Subscribe to this server
2. Enter your Tango Platform Name and Platform Key
3. Start managing your digital reward ecosystem from your favorite AI assistant
Who is this for?
- HR & Culture Managers — quickly send employee recognition rewards and verify account balances via simple AI commands.
- Marketing & Loyalty Teams — automate the distribution of campaign incentives and browse brand availability directly from the workspace.
- Operations Leads — monitor order histories and manage customer group funding via the AI assistant.
Built-in capabilities (12)
Create a new funding account
Create a new customer
Place a reward order
Get account balance
List available reward brands
Get customer details
Get currency exchange rates
Get order status
List accounts for a customer
List all customers
List funding sources
List recent orders
Why Pydantic AI?
Pydantic AI validates every Tango 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 Tango 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 Tango connection logic from agent behavior for testable, maintainable code
Tango in Pydantic AI
Tango and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Tango 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 Tango in Pydantic AI
The Tango 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
Tango for Pydantic AI
Every tool call from Pydantic AI to the Tango MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see my current account balance via AI?
Yes! Use the get_account tool and provide the Account Identifier. Your agent will retrieve the current balance and available funds for that specific funding account.
How do I find the correct ID (UTID) for a specific gift card brand?
Run the get_catalog query. The agent will retrieve the full list of available brands and items, each with its unique UTID required for placing orders.
Is it possible to track if a reward has been delivered?
Absolutely. Use the get_order tool and provide the Order ID. The agent will retrieve the status, delivery details, and even the credentials if the reward is ready.
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 Tango MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai