How to Use the Brilliant Made MCP in CrewAI

Deploy specialized agent crews to manage swag inventory and order fulfillment with CrewAI.

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Connect Brilliant Made MCP to CrewAI

Create your Vinkius account to connect Brilliant Made 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 Brilliant Made with CrewAI

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Coordinated swag operations in CrewAI

Assign a researcher agent to `list_products` while another agent handles `create_order`. CrewAI lets these agents share context so they don't step on each other's toes. You coordinate high-volume fulfillment without writing custom scripts. The MCP server acts as the shared toolset for your team of agents.

Automated fulfillment tracking in CrewAI

Monitor your shipping queue by having an agent call `list_fulfillment_orders` on a set interval. It flags delays before they become problems. You get full visibility into the process. The agent reports back only when it finds an order that needs human attention.

Product research tools for CrewAI

Let your research agent find the right items using `list_products` and `get_product_variant`. It narrows down options based on your specific requirements. Your crew stays focused on the goal. They handle the search and verify the details before you ever see a confirmation.

Setup guide

Set up Brilliant Made 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 Brilliant Made tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Brilliant Made 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 →

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