Bring Online Courses
to Pydantic AI
Learn how to connect Teachable (Extended) to Pydantic AI and start using 7 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Teachable (Extended) MCP Server?
Connect your Teachable school to any AI agent to streamline your course management and student operations through natural conversation.
What you can do
- Course Management — List all courses, filter by name, author, or publication status to keep track of your curriculum.
- User Operations — List, create, and update users. Search for students by email and manage their profiles without leaving your chat.
- Financial Tracking — Query transactions to monitor sales, refunds, and chargebacks across specific courses or users.
- Pricing & Plans — Access available pricing plans to understand your school's offer structure.
- Webhook Monitoring — List registered webhooks to ensure your external integrations are correctly configured.
How it works
- Subscribe to this server
- Enter your Teachable API Key
- Start managing your e-learning platform from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Course Creators — quickly check enrollment numbers and student details while planning content.
- Support Teams — update student names or find transaction records instantly to resolve tickets.
- School Administrators — monitor the health of the school through transaction and webhook audits.
Built-in capabilities (7)
Email is required. Create a new user in the Teachable school
Can be filtered by name, publish status, or author. List all courses in the Teachable school
List pricing plans in the Teachable school
Can be filtered by user, course, affiliate, dates, or refund/chargeback status. List transactions in the Teachable school
Can be filtered by email. Use search_after for pagination beyond 10,000 records. List all users in the Teachable school
List all registered webhooks
Update an existing user in the Teachable school
Why Pydantic AI?
Pydantic AI validates every Teachable (Extended) tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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 Teachable (Extended) 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 Teachable (Extended) connection logic from agent behavior for testable, maintainable code
Teachable (Extended) in Pydantic AI
Teachable (Extended) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Teachable (Extended) 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 | 4,000+ 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 Teachable (Extended) in Pydantic AI
The Teachable (Extended) 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 7 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
Teachable (Extended) for Pydantic AI
Every tool call from Pydantic AI to the Teachable (Extended) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I search for a specific student using their email address?
Yes! Use the list_users tool and provide the email address as a filter. The agent will return the user's details, including their ID and signup information.
Is it possible to see if a transaction has been refunded?
Absolutely. The list_transactions tool allows you to filter by is_fully_refunded. You can also filter by course ID or user ID to narrow down your search.
Can I update a user's name if they made a typo during registration?
Yes. Use the update_user tool with the student's user_id and the new name. The agent will process the update and confirm the changes in your Teachable school.
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 Teachable (Extended) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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