How to Use the Elevio MCP in CrewAI

Q: Can CrewAI agents read full Elevio articles?

Yes. A researcher agent can execute listknowledgearticles to get the index, then loop through getarticledetails to read the specific content of each guide.

Deploy specialized CrewAI agents to monitor, audit, and organize your Elevio documentation.

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Connect Elevio MCP to CrewAI

Create your Vinkius account to connect Elevio 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 Elevio with CrewAI

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Assign MCP tools to audit crews

You do not need to check your support center manually. You can assign the `quick_content_health_audit` tool to a specialized CrewAI analyst agent that monitors documentation volume. While the analyst checks the overall health, a secondary researcher agent fires `list_latest_article_updates`. They share memory, allowing the crew to build a complete report on what changed this week without human intervention.

Run autonomous category cleanup

Empty categories confuse users and clutter the interface. A dedicated moderation agent can sweep the system using `list_empty_knowledge_categories` to find missing links. Once the moderator finds the gaps, it passes the context to a content agent. That agent uses `search_knowledge_articles` to see if relevant articles exist but are miscategorized, fixing structural issues autonomously.

Monitor drafts and active modules

Support operations require constant oversight. You can build a supervisor agent that runs `list_active_modules` every hour to confirm your help widgets and search bars are actually online. At the same time, a separate agent tracks writer progress by calling `list_draft_knowledge_articles`. The crew cross-references these drafts against `get_article_details` to verify quality before alerting a human manager.

Setup guide

Set up Elevio 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 Elevio tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Elevio 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="Elevio Analyst",
        goal="Access and analyze Elevio data via MCP.",
        backstory="Expert analyst with direct Elevio access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Elevio 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 Elevio. 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 Elevio MCP in CrewAI

Pass the Vinkius endpoint directly into the mcps array in your Agent definition. For more control, use MCPServerHTTP and apply a tool_filter to restrict which agent gets which tool.

Yes. A researcher agent can execute list_knowledge_articles to get the index, then loop through get_article_details to read the specific content of each guide.

CrewAI relies on shared memory. If your audit agent pulls account limits using get_elevio_account_metadata, your reporting agent can instantly access that data to draft a summary.

The Python client supports stdio, SSE, and Streamable HTTP transports. Vinkius provides the HTTP endpoint, which handles the connection natively.

The agents process your knowledge categories, draft articles, and account metadata. Vinkius manages the authentication layer entirely. The server operates ephemerally, meaning no article text or search history is stored after the session ends.

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