How do I get a Google Classroom access token?

Go to [Google Cloud Console](https://console.cloud.google.com/), enable the Google Classroom API, create OAuth 2.0 credentials, and generate an access token with scopes: `classroom.courses`, `classroom.rosters`, `classroom.profile`. Use Google's OAuth Playground for quick testing.

Can I create and grade assignments?

Yes! Use `create_course_work` to create assignments with due dates and max points. Use `list_submissions` to see who turned in work, then `get_submission` to review individual student work. After grading, use `return_submission` to send it back to the student.

Can I manage student enrollment?

This MCP focuses on read-only operations for safety: listing students/teachers, viewing assignments, and tracking submissions. To add/remove students, use the Google Classroom web interface directly.

Google Classroom MCP Server for CrewAI 14 tools — connect in under 2 minutes

Name: Google Classroom
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 14 Tools Framework

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

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Google Classroom Specialist",
    goal="Help users interact with Google Classroom effectively",
    backstory=(
        "You are an expert at leveraging Google Classroom 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 Google Classroom "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 14 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Google Classroom MCP Server

Connect your Google Classroom to any AI agent and streamline your teaching workflows through natural conversation. Manage courses, create assignments, track student submissions, and grade work — all via AI commands.

When paired with CrewAI, Google Classroom becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Google Classroom 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

Course Management — List, create, and update courses with full details
Roster Tracking — List enrolled students and assigned teachers for any course
Assignments — Create coursework, set due dates, and track all assignments
Submission Monitoring — Check who turned in work, who's late, and who hasn't submitted
Grading — Review individual submissions, return graded work to students
Announcements — Post important updates to the course stream

The Google Classroom MCP Server exposes 14 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.

How to Connect Google Classroom to CrewAI via MCP

Follow these steps to integrate the Google Classroom MCP Server with CrewAI.

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 14 tools from Google Classroom

Why Use CrewAI with the Google Classroom MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Google Classroom 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

Google Classroom + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Google Classroom 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 Google Classroom, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Google Classroom 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 Google Classroom against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Google Classroom MCP Tools for CrewAI (14)

These 14 tools become available when you connect Google Classroom to CrewAI via MCP:

create_announcement

Announcements appear in the course stream and can be used for important updates, reminders, or general communication. Post a new announcement to a Google Classroom course

create_course

Returns the new course ID for future reference. Only users with appropriate permissions can create courses. Create a new Google Classroom course

create_course_work

The assignment will be visible to all students in the course. Supports assignments, quizzes, and materials types. Create a new assignment or coursework in Google Classroom

get_course

Use the course ID obtained from list_courses. Get details of a specific Google Classroom course

get_submission

Get a specific student's submission details

list_announcements

Use this to check recent course announcements and important updates. List all announcements in a Google Classroom course

list_course_work

Returns assignment title, due date, state (DRAFT/PUBLISHED), max points, and creation time. Use this to track all assignments and their deadlines. List all assignments and coursework for a Google Classroom course

list_courses

Essential first step to identify which course to work with before querying students, assignments, or submissions. List all Google Classroom courses

list_students

Use this to check enrollment, identify students for grading, or verify class roster. List all students enrolled in a Google Classroom course

list_submissions

Returns student ID, submission state (NEW/CREATED/TURNED_IN/RETURNED), grade, and late status. List student submissions for a specific assignment

list_teachers

List all teachers of a Google Classroom course

return_submission

This is typically done after the teacher has reviewed and graded the work. The student will be notified that their work has been returned. Return a graded assignment to the student

turn_in_submission

The student must have created the submission first. This is equivalent to clicking "Turn In" in the Classroom UI. Turn in a student's assignment submission

update_course

Requires the course ID and at least one field to update. Update an existing Google Classroom course

Example Prompts for Google Classroom in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Google Classroom immediately.

"List all my courses and show students in Math 101."

"Create an assignment called 'Chapter 5 Problems' due 2024-05-15 for course 12345, max 100 points."

"Show me who turned in the Chapter 5 assignment."

Troubleshooting Google Classroom MCP Server with CrewAI

Common issues when connecting Google Classroom 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.

Google Classroom + CrewAI FAQ

Common questions about integrating Google Classroom 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.