How to Use the Lemon Squeezy MCP in AutoGen
Build multi-agent AutoGen debates to verify orders, manage subscriptions, and audit Lemon Squeezy stores without human intervention.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Lemon Squeezy MCP to AutoGen
Create your Vinkius account to connect Lemon Squeezy 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.
Negotiate subscription cancellations in AutoGen
The `cancel_subscription` tool terminates billing agreements on Lemon Squeezy while preserving customer access until the end of the current term. Inside AutoGen, a customer retention agent and a billing agent debate whether to offer a discount before executing this call. This conversation ensures your AutoGen workflows do not lose Lemon Squeezy revenue to accidental clicks. The billing agent only triggers the cancel tool once both agents agree that retention efforts failed.
Audit store catalogs with multi-agent consensus
The `list_all_products` tool outputs every digital item available in your Lemon Squeezy store. An AutoGen inventory agent and a pricing agent analyze this list to verify that all SKUs match your master spreadsheet. They cross-reference the output with `get_product_details` to check for Lemon Squeezy pricing discrepancies. If the AutoGen agents find an error, they flag it for human review before updating any frontend pages.
Verify order fraud using this MCP Server
The `get_order_details` tool retrieves the full transaction payload for a specific Lemon Squeezy purchase. An AutoGen security agent inspects the billing address while a customer agent checks historical orders using `list_all_orders`. These AutoGen agents debate the Lemon Squeezy fraud risk score in a structured conversation loop. They block or approve fulfillment based on the consensus reached during their analysis.
Set up Lemon Squeezy 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 Lemon Squeezy 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="Lemon Squeezy_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Lemon Squeezy 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="Lemon Squeezy_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Lemon Squeezy 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 Lemon Squeezy. 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 Lemon Squeezy MCP in AutoGen
Use it with your favorite AI tools
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