How to Use the Innform MCP in CrewAI

Q: Can CrewAI agents collaborate to unfreeze an Innform user?

Yes. An audit agent can verify completion using listcompletedassignments, then instruct an admin agent to call unfreezeuser once the training requirements are met.

Q: How do CrewAI agents share data about Innform groups?

CrewAI uses shared memory. When one agent calls listgroups, the resulting group IDs and names are stored in the shared context, allowing other agents to use that data for updates.

Q: How does the system protect sensitive user details and assignment lists?

All calls to getuserdetails and listoverdueassignments are handled via ephemeral, end-to-end encrypted tunnels. No learner PII is stored on our servers, keeping your MCP audits completely private.

Deploy a crew of specialized AI agents to manage your Innform compliance and user lifecycles autonomously.

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Connect Innform MCP to CrewAI

Create your Vinkius account to connect Innform to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Innform with CrewAI

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Multi-agent compliance teams using CrewAI

Let specialized agents run your training operations. Using this MCP Server, one agent can monitor compliance using `list_overdue_assignments`, while a separate manager agent decides whether to execute `freeze_user` on delinquent accounts. This division of labor keeps your LMS clean. The agents share context through CrewAI's memory system, ensuring they never take action without reviewing the user's full history first.

Autonomous learner onboarding

Automating your entire hiring training pipeline is simple. Your crew can detect new hires, trigger `invite_user` to get them into the system, and assign them to the correct cohorts using `list_groups`. By letting agents collaborate, you eliminate manual data entry. The onboarding agent hands off the new user's ID to the setup agent, who configures their profile instantly.

Automated training audits

Stop running manual compliance audits every week. An audit agent can pull records using `list_completed_assignments` and cross-reference them with active user profiles from `list_users`. The agent compiles a clean report of who is up-to-date and who needs a nudge, then passes it to a notification agent to send out reminders.

Setup guide

Set up Innform MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Innform tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Innform Analyst",
    goal="Access and analyze Innform data via MCP.",
    backstory="Expert analyst with direct Innform access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Innform transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Innform Analyst",
        goal="Access and analyze Innform data via MCP.",
        backstory="Expert analyst with direct Innform access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Innform transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Innform. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Innform MCP in CrewAI

Pass your server endpoint URL directly into the agent's MCP configuration array during initialization. The agent will auto-discover tools like `get_user_details` and use them as needed.

Yes. An audit agent can verify completion using `list_completed_assignments`, then instruct an admin agent to call `unfreeze_user` once the training requirements are met.

CrewAI uses shared memory. When one agent calls `list_groups`, the resulting group IDs and names are stored in the shared context, allowing other agents to use that data for updates.

Yes. You can set up a manager agent that oversees worker agents, ensuring that actions like updating profiles are reviewed before the MCP tool runs.

All calls to `get_user_details` and `list_overdue_assignments` are handled via ephemeral, end-to-end encrypted tunnels. No learner PII is stored on our servers, keeping your MCP audits completely private.

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