How to Use the Brilliant Made MCP in AutoGen
Let AutoGen agents debate inventory levels and coordinate swag orders through autonomous conversations.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Brilliant Made MCP to AutoGen
Create your Vinkius account to connect Brilliant Made to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Deploy an MCP Server for AutoGen swag workflows
This MCP Server allows multiple autonomous AutoGen agents to discuss and execute Brilliant Made swag logistics. An AutoGen procurement agent can run `get_inventory_status` while a finance agent evaluates budget constraints before running `create_order` in Brilliant Made. This conversational approach ensures that no Brilliant Made order is placed without AutoGen verifying stock levels. The AutoGen agents talk to each other to resolve conflicts before executing the final Brilliant Made purchase.
Automated gift card management and verification
This toolset lets your AutoGen agent groups manage corporate incentives through structured discussion using Brilliant Made endpoints. One AutoGen agent can list current cards using `list_gift_cards` while another agent verifies balances and runs `create_gift_card` when Brilliant Made triggers are met. The entire negotiation happens autonomously within your configured AutoGen group chat using Brilliant Made swag parameters. You define the rules, and the AutoGen agents use the tools to execute the correct Brilliant Made promotional actions based on consensus.
Multi-agent tracking of fulfillment orders
This integration helps you monitor complex Brilliant Made shipping pipelines using specialized AutoGen agent roles. Your AutoGen support agent can call `list_fulfillment_orders` and share the payload with a customer-facing agent who drafts the Brilliant Made update. If a Brilliant Made order is stuck, an AutoGen supervisor agent can step in and run `cancel_order` based on the conversation history. This distributed AutoGen decision-making model prevents errors and keeps your Brilliant Made logistics pipeline moving.
Set up Brilliant Made MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Brilliant Made tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Brilliant Made_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Brilliant Made data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Brilliant Made_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Brilliant Made data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Brilliant Made. 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 Brilliant Made MCP in AutoGen
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