Can I check a student's attendance history via AI?

Yes! Use the `list_student_attendance` tool and provide the Student ID. Your agent will retrieve the complete attendance record for that student.

How do I add a new student to the SIS using the agent?

Use the `create_student_profile` action. Provide the first name, last name, and email to register the new student record in Classe365 instantly.

Is it possible to see exam scores via AI?

Absolutely. Use the `list_exam_assessments` query. The agent will retrieve a list of assessments and scores recorded in your academy's account.

INSTANT PLUG AND PLAY

Classe365 MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 7 tools to Create Student Profile, Get Student Details, List Academic Records, and more

Name: Classe365
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 7 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Classe365 through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Use with Your AI Agent

Ask AI about this App Connector for OpenAI Agents SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Classe365 app connector for OpenAI Agents SDK is a standout in the Human Resources category — giving your AI agent 7 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

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

        agent = Agent(
            name="Classe365 Assistant",
            instructions=(
                "You help users interact with Classe365. "
                "You have access to 7 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Classe365"
        )
        print(result.final_output)

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 Classe365 MCP Server

Connect your Classe365 student management system to any AI agent and simplify how you coordinate your educational institution, student directory, and academic records through natural conversation.

The OpenAI Agents SDK auto-discovers all 7 tools from Classe365 through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Classe365, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Student Lifecycle — List all students, create new academic profiles, and retrieve detailed metadata for individual enrollments.
Academic Oversight — List academic departments, sections, and classes to understand your institution's hierarchy.
Performance Monitoring — List and query student attendance history and exam assessment scores via AI.
School Operations — Verify configured subjects and class distributions directly from the agent.
Data Insights — Fetch complete student metadata including contact info and course progress.
Administrative Efficiency — Automate student registrations and record-keeping without leaving your workspace.

The Classe365 MCP Server exposes 7 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 7 Classe365 tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Classe365 through Vinkius, your AI agent gets direct access to every tool listed below — spanning student-information-system, academic-management, admissions-tracking, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_student_profile

Add a new student

get_student_details

Get details for a specific student

list_academic_records

List academic departments and sections

list_exam_assessments

List assessments and scores

list_school_classes

List configured classes

list_student_attendance

List student attendance history

list_students

List Classe365 students

Connect Classe365 to OpenAI Agents SDK via MCP

Follow these steps to wire Classe365 into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 7 tools from Classe365

Why Use OpenAI Agents SDK with the Classe365 MCP Server

OpenAI Agents SDK provides unique advantages when paired with Classe365 through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Classe365 + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Classe365 MCP Server delivers measurable value.

Automated workflows: build agents that query Classe365, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Classe365, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Classe365 tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Classe365 to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Classe365 in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Classe365 immediately.

"List all active students in my school account."

"Show me the attendance record for student 'std_10293'."

"Create a student profile for 'Anna White' (anna@example.com)."

Troubleshooting Classe365 MCP Server with OpenAI Agents SDK

Common issues when connecting Classe365 to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Classe365 + OpenAI Agents SDK FAQ

Common questions about integrating Classe365 MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.