How to Use the AcademyOfMine MCP in Pydantic AI

Q: How do I configure the AcademyOfMine MCP Server toolset in Pydantic AI?

Install pydantic-ai-slimmcp and initialize MCPToolset with your Vinkius HTTP URL. Pass this toolset directly into your agent's toolsets parameter.

Q: Can I query AcademyOfMine course curriculums using Pydantic AI?

Yes, the agent calls getcoursecurriculum to inspect course structures. The returned JSON is validated against strict Pydantic schemas before your agent reads it.

Q: How does Pydantic AI protect my AcademyOfMine portal settings?

The getportalsettings tool is wrapped in zero-trust V8 execution. Your administrative credentials are never exposed to the LLM or stored in the agent's memory.

Build type-safe AcademyOfMine LMS integrations with runtime validation using Pydantic AI.

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Connect AcademyOfMine MCP to Pydantic AI

Create your Vinkius account to connect AcademyOfMine to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup AcademyOfMine with Pydantic AI

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Validate course creation with Pydantic AI

The `create_course` tool requires structured inputs that Pydantic AI validates at runtime before hitting your LMS API. If your LLM attempts to pass a malformed syllabus, the framework blocks the call instantly. When updating existing paths, `update_course` ensures that your changes match the expected database schema. This prevents database corruption and keeps your LMS catalog pristine.

Type-safe student enrollment MCP Server

This AcademyOfMine MCP Server relies on `enroll_student` to register users into active courses with strict type checks. The agent cannot pass invalid IDs or malformed email strings to your portal. If an enrollment fails or a student is removed via `unenroll_student`, the response is parsed back into a validated Python model. You get explicit error messages instead of silent runtime failures.

Query LMS records with guaranteed schemas

The `get_user_details` tool returns learner profiles that match strict internal typing rules. Your agent can confidently extract emails, progress metrics, and registration dates without worrying about missing fields. For broader audits, the agent uses `list_users` to scan the entire portal. Pydantic AI processes the list, ensuring every record conforms to your application's data models.

Setup guide

Set up AcademyOfMine MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "academyofmine-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to AcademyOfMine tools.",
)

result = await agent.run("List recent AcademyOfMine transactions")
print(result.output)

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Common questions about AcademyOfMine MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]` and initialize `MCPToolset` with your Vinkius HTTP URL. Pass this toolset directly into your agent's `toolsets` parameter.

The framework raises a validation error immediately. This prevents your agent from processing corrupt or incomplete user details in downstream code.

Yes, the agent calls `get_course_curriculum` to inspect course structures. The returned JSON is validated against strict Pydantic schemas before your agent reads it.

No, the MCP Server runs in a hosted Vinkius sandbox. Your Pydantic AI script connects to it over a secure SSE or HTTP stream.

The `get_portal_settings` tool is wrapped in zero-trust V8 execution. Your administrative credentials are never exposed to the LLM or stored in the agent's memory.

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