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How to Use the Konnektive MCP in CrewAI

Deploy autonomous agent crews to manage your Konnektive CRM and fulfillment operations with CrewAI.

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Connect Konnektive MCP to CrewAI

Create your Vinkius account to connect Konnektive 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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Deploy Support Crews with CrewAI

Assign an investigator agent to run `query_konnektive_customers` through the MCP Server when a support ticket opens. This agent gathers the user profile and hands the context off to a resolution agent. The crew works sequentially to build a complete picture of the account. The resolution agent then calls `get_order_details` to find the specific purchase. Because they share memory, the second agent already knows exactly which order ID to look for based on the investigator's findings.

Monitor Fulfillment Automatically

Set up a logistics agent to constantly poll `list_fulfillment_houses`. It maps out your available shipping centers and evaluates their current load. When an order comes in, an execution agent uses `update_order_shipping_address` to route the package to the optimal warehouse. The entire process runs autonomously in the background without human intervention.

Audit Transactions via MCP Server

Build a financial compliance crew that triggers `query_konnektive_transactions` to scan for high-risk payments. The monitoring agent flags anything suspicious based on your custom rules. A secondary auditor agent then pulls `get_konnektive_audit_logs` to trace the history of the flagged transaction. It compiles a report of who touched the record and escalates it to your finance team.

Setup guide

Set up Konnektive MCP in CrewAI

Prerequisites

  • Python 3.10+ installed
  • crewai package (pip install crewai)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install CrewAI

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

  2. 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. 3

    Kick off your crew

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

crew.py
from crewai import Agent, Task, Crew

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

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

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

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Konnektive MCP in CrewAI

Pass your Vinkius endpoint directly into the mcps array when defining your Agent. For more granular control, import MCPServerHTTP from crewai.mcp and use tool_filter.
Yes. You can assign list_konnektive_products to a sales agent and restrict update_order_shipping_address to a logistics agent using the tool_filter parameter.
Agents share a common memory pool. When your research agent pulls get_order_details, the extracted JSON is available to the action agent in the next step of the sequence.
The Python client supports stdio, SSE, and Streamable HTTP. Just provide the correct URL scheme and the underlying client handles the connection routing.
When your compliance agent runs get_konnektive_audit_logs, the request executes in a zero-trust environment. The ephemeral sandbox processes the system records, returns the text to your crew, and immediately self-destructs.

Start using the Konnektive MCP today

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