How can I check the training progress of a specific team?

Use the `get_stats` tool filtered by Group ID. Your agent will retrieve completion rates and average scores for that specific team.

Can I create new learners via the AI agent?

Yes, you can use the `create_user` tool to register new learners on your 360Learning platform directly from your conversation.

How do I browse available training courses?

Use the `list_courses` tool to view the catalog of available courses. You can then use `get_course` to see more specific details about any curriculum.

360Learning MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: 360Learning
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to 360Learning through Vinkius, pass the Edge URL in the `mcps` parameter and every 360Learning 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="360Learning Specialist",
    goal="Help users interact with 360Learning effectively",
    backstory=(
        "You are an expert at leveraging 360Learning 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 360Learning "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

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

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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 360Learning MCP Server

Empower your corporate education strategy with 360Learning, the collaborative learning platform now fully integrated with your AI agent. By connecting 360Learning via the Model Context Protocol, you transform learning management from a complex administrative task into a natural conversation. Your agent can now seamlessly provision learners, audit course completions, and retrieve real-time training statistics without you ever navigating a LMS dashboard. It’s the smartest way to scale knowledge sharing and ensure your team stays ahead of the curve.

When paired with CrewAI, 360Learning becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call 360Learning 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

User Management — List, create, and update learners and admins within your platform.
Course Catalog — Browse available courses, view lesson details, and check enrollment status.
Learning Paths — Manage structured training paths and monitor group progress across curriculum.
Engagement Stats — Access completion rates, time spent, and assessment scores to gauge training effectiveness.
Group Organization — List and manage departments or training cohorts for targeted learning delivery.

The 360Learning MCP Server exposes 6 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 360Learning to CrewAI via MCP

Follow these steps to integrate the 360Learning 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 6 tools from 360Learning

Why Use CrewAI with the 360Learning MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with 360Learning 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

360Learning + CrewAI Use Cases

Practical scenarios where CrewAI combined with the 360Learning MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries 360Learning 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 360Learning, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain 360Learning 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 360Learning against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

360Learning MCP Tools for CrewAI (6)

These 6 tools become available when you connect 360Learning to CrewAI via MCP:

create_user

Requires the email, first name, and last name of the user. Register a new learner, author, or administrator account

get_course

Get technical details and the lesson overview for a specific course

get_stats

You must filter by either Group ID, User ID, or Course ID. Retrieve training completion rates and assessment scores

list_courses

Use this to find a specific Course ID to check enrollments or detailed lessons. Browse the catalog of available training courses

list_groups

Useful for finding a specific Group ID for reporting strategies. List all training groups, departments, or cohorts in the platform

list_users

Use this to find specific learner profiles. List all active learners and administrators in the 360Learning platform

Example Prompts for 360Learning in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with 360Learning immediately.

"List all active users in my 360Learning platform."

"Show me the training statistics for the 'Marketing' group."

"List all available courses in the catalog."

Troubleshooting 360Learning MCP Server with CrewAI

Common issues when connecting 360Learning 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.

360Learning + CrewAI FAQ

Common questions about integrating 360Learning 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.