Can I track completion rates across my entire team at once?

Yes. List all students associated with your partner API key, then ask your agent to summarize each student's completion percentage and pending projects. Get a full team progress report in a single conversation — no spreadsheets, no manual exports from the OpenClassrooms dashboard.

What data do I get about mentoring sessions?

The agent pulls session date, time, mentor name, session status (completed, scheduled, or missed), and the student linked to each session. This is useful for auditing mentorship quality and identifying students who are missing their scheduled sessions.

Is this API available to everyone or only to OpenClassrooms partners?

The OpenClassrooms API is restricted to approved partners. You need an active partnership agreement with OpenClassrooms to obtain production API credentials. If you're already a partner, your account manager can provide the API key. This integration is designed for organizations using OpenClassrooms for team training.

OpenClassrooms MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: OpenClassrooms
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OpenClassrooms 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 OpenClassrooms "
            "(9 tools)."
        ),
    )

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

asyncio.run(main())

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About OpenClassrooms MCP Server

Connect your OpenClassrooms partner account to any AI agent and get full visibility into courses, student progress, and diploma paths — all through natural conversation.

Pydantic AI validates every OpenClassrooms tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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 Catalog — List available courses, search by keyword (React, Python, Data Science), and view detailed syllabi with skill competencies
Diploma Paths — Browse career-focused paths with all required courses, projects, and estimated completion times
Student Tracking — List enrolled students under your partner account and check individual progress including project validations and completion percentages
Mentoring Sessions — View past and upcoming mentoring sessions with session dates, mentors, and status
Certificates — Retrieve verified completion certificates for any student with public verification IDs

The OpenClassrooms MCP Server exposes 9 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 OpenClassrooms to Pydantic AI via MCP

Follow these steps to integrate the OpenClassrooms 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 9 tools from OpenClassrooms with type-safe schemas

Why Use Pydantic AI with the OpenClassrooms MCP Server

Pydantic AI provides unique advantages when paired with OpenClassrooms 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 OpenClassrooms integration code

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

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

OpenClassrooms + Pydantic AI Use Cases

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

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

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

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

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

OpenClassrooms MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect OpenClassrooms to Pydantic AI via MCP:

certificats_etudiant

Consulter les certificats de réussite obtenus par un étudiant

consulter_cours

Consulter le détail profond d'un cours spécifique

consulter_parcours

Consulter la taxonomie détaillée d'un parcours diplômant spécifique

lister_cours

Lister les cours disponibles sur OpenClassrooms (Pagination active)

lister_etudiants

Lister les étudiants inscrits sous cette clé d'API (Partenaires)

lister_parcours

Lister l'intégralité des parcours diplômants OpenClassrooms

progression_etudiant

Consulter la progression précise d'un étudiant métier

rechercher_cours

Rechercher des cours OpenClassrooms dynamiquement par mots-clés

sessions_mentorat

Lister les sessions de mentorat vidéo programmées

Example Prompts for OpenClassrooms in Pydantic AI

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

"Search for courses about Python data analysis."

"How is Maria Silva progressing in her diploma path?"

"Which students have earned certificates this month?"

Troubleshooting OpenClassrooms MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OpenClassrooms + Pydantic AI FAQ

Common questions about integrating OpenClassrooms 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 OpenClassrooms MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.