How to Use the Sellfy MCP in CrewAI
Deploy autonomous agent crews to monitor and manage your Sellfy store 24/7 with CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Sellfy MCP to CrewAI
Create your Vinkius account to connect Sellfy to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Build an Autonomous Monitoring Crew
This toolset is perfect for a multi-agent setup in CrewAI. Assign one agent the role of "Order Monitor." Its only job is to run `list_orders` every minute. When it detects a new order, it passes the order ID to a "Fraud Analyst" agent. That second agent then uses `get_order_details` and `get_customer_details` to look for suspicious patterns. This isn't one agent doing everything; it's a specialized team using this Sellfy MCP connection to run your store's security watch.
The Catalog Management CrewAI Team
Divide and conquer your catalog management. A "Scout" agent can be tasked with finding new products to add from an external source. Once it has the data, it hands it off to a "Loader" agent, whose sole purpose is to use the `create_product` tool on the Sellfy MCP server. Meanwhile, an "Auditor" agent can periodically run `list_products` and `list_product_categories` to ensure everything is organized correctly. By defining clear roles, your CrewAI team can manage a complex catalog without any human intervention.
Run a Subscription Analytics Crew
Get deeper insights into your recurring revenue. Create a "Data Gatherer" agent that uses `list_subscriptions` to get a list of all active subscriptions and `get_subscription_details` to pull the specifics for each one. It passes this raw data to an "Analyst" agent that calculates metrics like monthly recurring revenue or churn rate. Finally, a "Reporter" agent takes the numbers and formats a daily summary. Each agent has one job, and together they produce valuable business intelligence.
Set up Sellfy MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Sellfy tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Sellfy Analyst",
goal="Access and analyze Sellfy data via MCP.",
backstory="Expert analyst with direct Sellfy access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Sellfy transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="Sellfy Analyst",
goal="Access and analyze Sellfy data via MCP.",
backstory="Expert analyst with direct Sellfy access.",
tools=mcp_tools,
)
task = Task(
description="List recent Sellfy transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Sellfy. 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 Sellfy MCP in CrewAI
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