How do I get an eduMe API Key?

Log in to your eduMe dashboard, navigate to **Settings > API**, and you can generate or retrieve your unique API Key from there. API access may require an enterprise-level plan.

Can the agent assign courses to users?

This integration currently focuses on listing and auditing training data. Assigning courses or creating new users should be managed via the eduMe dashboard or specific enrollment API endpoints.

Does the integration show real-time completion?

Yes, you can use the list_training_courses or get_user_training_profile tools to retrieve the latest completion rates and statuses as reported by the eduMe platform.

eduMe MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: eduMe
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect eduMe through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to eduMe "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in eduMe?"
    )
    print(result.data)

asyncio.run(main())

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* 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

About eduMe MCP Server

Integrate eduMe, the leading mobile-first training platform for the deskless workforce, directly into your AI workflow. Manage your training courses and modules, track trainee profiles and completion rates, monitor team performance, and oversee your organizational learning metadata using natural language.

Pydantic AI validates every eduMe 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.

What you can do

Course Oversight — List and retrieve detailed information and completion metrics for all your mobile training courses.
Trainee Intelligence — Monitor user training profiles, identifying completed courses, active enrollments, and organizational team memberships.
Team Management — Access and monitor all training teams and user groups configured in your eduMe account.
Learning Auditing — Retrieve high-level summaries of team activity, course engagement, and organizational training health.

The eduMe MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect eduMe to Pydantic AI via MCP

Follow these steps to integrate the eduMe MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from eduMe with type-safe schemas

Why Use Pydantic AI with the eduMe MCP Server

Pydantic AI provides unique advantages when paired with eduMe through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your eduMe integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your eduMe connection logic from agent behavior for testable, maintainable code

eduMe + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the eduMe MCP Server delivers measurable value.

Type-safe data pipelines: query eduMe with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple eduMe tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query eduMe and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock eduMe responses and write comprehensive agent tests

eduMe MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect eduMe to Pydantic AI via MCP:

get_course_details

Get detailed settings and module list for a specific training course

get_edume_account_metadata

Retrieve metadata and limits for your eduMe account

get_user_training_profile

Get full training history and profile for a specific user

list_latest_training_content

Identify the most recently created or updated training courses

list_top_performing_courses

Identify courses with the highest completion or engagement rates (mock logic)

list_trained_users

List all users registered in your eduMe training platform

list_training_courses

List all mobile training courses available in eduMe

list_training_teams

List all teams and user groups configured in your eduMe account

quick_team_training_audit

Retrieve a high-level summary of team activity and member counts

search_trainees_by_keyword

Search for users using a name keyword or external identifier

Example Prompts for eduMe in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with eduMe immediately.

"List all mobile training courses."

"Show me the training profile for user 'john_doe'."

"Which teams have the lowest course engagement?"

Troubleshooting eduMe MCP Server with Pydantic AI

Common issues when connecting eduMe to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

eduMe + Pydantic AI FAQ

Common questions about integrating eduMe MCP Server with Pydantic AI.

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 eduMe MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.