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 CrewAIGive CrewAI 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 Framework

Connect your CrewAI agents to Classe365 through Vinkius, pass the Edge URL in the `mcps` parameter and every Classe365 tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

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The Classe365 app connector for CrewAI 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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Classe365 Specialist",
    goal="Help users interact with Classe365 effectively",
    backstory=(
        "You are an expert at leveraging Classe365 tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Classe365 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Classe365 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Classe365 tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI

When CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 7 tools from Classe365

Why Use CrewAI with the Classe365 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Classe365 through the Model Context Protocol.

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

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter 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

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Classe365 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Classe365 MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Classe365 for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Classe365, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Classe365 tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Classe365 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Classe365 in CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Classe365 to CrewAI through the Vinkius, and how to resolve them.

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.

Classe365 + CrewAI FAQ

Common questions about integrating Classe365 MCP Server with CrewAI.

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.