Bring Online Courses
to CrewAI
Learn how to connect Teachable (Extended) to CrewAI 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 CrewAI?
When paired with CrewAI, Teachable (Extended) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Teachable (Extended) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Teachable (Extended) in CrewAI
Teachable (Extended) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Teachable (Extended) to CrewAI 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 CrewAI
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 CrewAI 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 CrewAI
Every tool call from CrewAI 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 CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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