How to Use the OpenPanel MCP in CrewAI
Equip your CrewAI agents with OpenPanel analytics. Assign roles for tracking, identifying, and acting on user data autonomously.
Works with every AI agent you already use
…and any MCP-compatible client
Connect OpenPanel MCP to CrewAI
Create your Vinkius account to connect OpenPanel to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Assign a Dedicated Analytics Agent
With CrewAI, you can create an agent whose only job is to watch user activity and report it. This 'Analytics Agent' would use the `track_event` tool every time another agent in the crew completes a significant action. This separates concerns cleanly. Your 'Writer Agent' doesn't need to know about analytics; it just does its job. The Analytics Agent observes the shared state and calls `track_event`, keeping your telemetry logic isolated and easy to manage.
Create User-Aware Agent Crews
Start your crew's process with an 'Identifier Agent' that calls `identify_user`. The user's profile from OpenPanel then becomes part of the crew's shared context, available to all other agents. Now, a 'Personalization Agent' can act on that data. It can check the user's properties and direct the crew's next steps, creating a system where agent behavior changes based on who the user is. This is all possible with one MCP server.
Automate User Metric Management
You can build a 'Billing Agent' that uses `increment_property` and `decrement_property`. Its role is to monitor resource usage and update a user's balance in OpenPanel. For example, if a 'Generator Agent' creates five images, the Billing Agent sees this and calls `increment_property('images_created', 5)`. It's a simple way to build autonomous, meter-based systems using a crew of specialized agents.
Set up OpenPanel 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 OpenPanel tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="OpenPanel Analyst",
goal="Access and analyze OpenPanel data via MCP.",
backstory="Expert analyst with direct OpenPanel access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent OpenPanel 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="OpenPanel Analyst",
goal="Access and analyze OpenPanel data via MCP.",
backstory="Expert analyst with direct OpenPanel access.",
tools=mcp_tools,
)
task = Task(
description="List recent OpenPanel 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 OpenPanel. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about OpenPanel MCP in CrewAI
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