How to Use the Magento (Adobe Commerce) MCP in CrewAI

Q: How do I limit which Magento (Adobe Commerce) tools a CrewAI agent can use?

Use the toolfilter option in MCPServerHTTP. This lets you restrict your support agent to mg.getcustomer while keeping billing tools like mg.listinvoices reserved only for your finance agent.

Q: What python packages do I need for this setup?

You need to run pip install crewai "crewaitools". This installs the core framework along with the necessary HTTP client libraries to connect to the Vinkius MCP endpoint.

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Connect Magento (Adobe Commerce) MCP to CrewAI

Create your Vinkius account to connect Magento (Adobe Commerce) 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 Magento (Adobe Commerce) with CrewAI

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Audit Magento inventory with a CrewAI MCP Server team

Instead of relying on a single script, you can deploy a team of specialized agents. One CrewAI agent can focus on identifying low-stock items using `mg.get_stock`. Another agent analyzes the sales velocity of those items by pulling recent orders. They share memory to make smart restocking decisions. If stock is low, they look up the manufacturer details using `mg.get_product` and draft a reorder email, all without human intervention.

Autonomous customer support routing

Set up a customer service crew that handles inquiries autonomously. A triaging agent receives the customer's request and queries `mg.search_customers` to find their profile. It then hands the ticket to a specialized billing agent. The billing agent calls `mg.list_invoices` to check for payment issues. Because CrewAI agents share context, the billing agent knows the customer's history without having to run duplicate database queries.

Smart order reconciliation

Let your agents reconcile sales data at the end of the day. One agent searches recent transactions using `mg.search_orders`. It passes the order IDs to a verification agent that pulls the full details via `mg.get_order`. A third agent checks these orders against your store settings using `mg.get_store_config`. This multi-agent pipeline catches discrepancies between your payment gateway and your Magento database automatically.

Setup guide

Set up Magento (Adobe Commerce) 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 Magento (Adobe Commerce) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Magento (Adobe Commerce) 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 Magento (Adobe Commerce). 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 Magento (Adobe Commerce) MCP in CrewAI

You can pass the Vinkius HTTP URL directly into your agent's mcps list. For more control, use MCPServerHTTP from crewai.mcp and apply a tool_filter to limit which agents can access tools like mg.get_order.

Yes, CrewAI features shared memory. If one agent fetches product details using mg.get_product, that context is immediately available to other agents in the crew. This prevents redundant API calls to your store.

Use the tool_filter option in MCPServerHTTP. This lets you restrict your support agent to mg.get_customer while keeping billing tools like mg.list_invoices reserved only for your finance agent.

You need to run pip install crewai "crewai[tools]". This installs the core framework along with the necessary HTTP client libraries to connect to the Vinkius MCP endpoint.

We run the MCP Server inside an ephemeral, zero-trust sandbox. When your agents query customer databases via mg.search_customers, the PII is processed in memory and never written to disk. Vinkius acts as a secure pass-through with zero persistent storage.

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