Bring Churn Reduction
to Pydantic AI
Learn how to connect Upzelo to Pydantic AI and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Upzelo MCP Server?
Connect your Upzelo churn management account to any AI agent and simplify how you retain customers and manage subscription lifecycles through natural conversation.
What you can do
- Customer Management — List and search customer records, and update profile data for better segmentation and targeting.
- Retention Flows — List available flows and manually trigger retention sequences for customers at risk of cancelling.
- Subscription Tracking — Query all tracked subscriptions and update statuses or trial details programmatically.
- Flow Monitoring — Check the real-time status and outcomes of active flow sessions to verify retention success.
- External ID Sync — Link your internal system identifiers to Upzelo customer records for seamless integration.
How it works
1. Subscribe to this server
2. Enter your Upzelo App ID and API Key (found in your developer settings)
3. Start managing your retention strategy from Claude, Cursor, or any MCP client
Who is this for?
- Customer Success Managers — quickly trigger retention flows and check customer health via simple AI commands.
- Product Operations — monitor subscription statuses and sync customer data directly from the workspace.
- Business Growth Teams — get instant insights into flow performance and active retention sessions.
Built-in capabilities (10)
Get details for a specific customer
Get details for a specific flow
Check the status of a flow session
Get details for a specific subscription
List all customers in Upzelo
List all retention flows
List all subscriptions
Used for segmentation and targeting. Create or update a customer record
Initialize a flow for a customer
Update subscription attributes
Why Pydantic AI?
Pydantic AI validates every Upzelo tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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 Upzelo 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 Upzelo connection logic from agent behavior for testable, maintainable code
Upzelo in Pydantic AI
Upzelo and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Upzelo 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 Upzelo in Pydantic AI
The Upzelo 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 10 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
Upzelo for Pydantic AI
Every tool call from Pydantic AI to the Upzelo MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I manually start a retention flow for a customer via AI?
Yes! Use the start_flow tool and provide the Flow ID, Customer ID, and Subscription ID. This will initialize the retention experience for that user immediately.
How do I see if a customer successfully stayed after a flow?
Run the get_flow_session query with the specific Session ID. It will return the outcome and status of the retention attempt.
Is it possible to update a subscription's status via AI?
Absolutely. Use the update_subscription tool by providing the Subscription ID and the new status to synchronize data between your systems and Upzelo.
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 Upzelo MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai