How to Use the EyePop.ai MCP in CrewAI

Q: How do I limit tool access?

Use the toolfilter in your CrewAI setup. This ensures only the correct agents have the authority to call sensitive tools like createpop.

Deploy specialized vision agents in CrewAI using the EyePop.ai MCP Server.

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Connect EyePop.ai MCP to CrewAI

Create your Vinkius account to connect EyePop.ai 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 EyePop.ai with CrewAI

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Perplexity

Role-based vision analysis

Assign a dedicated monitor agent in CrewAI to run `analyze_video` continuously. Other agents in your crew receive these detection results to perform specialized tasks like logging or reporting. This segregation of duty keeps your main agent focused. The vision agent handles the heavy lifting, while the coordinator agent manages the flow of information.

Shared model intelligence

Your agents call `list_models` to determine which detection model is best for a specific scene. A research agent can identify the right model, and an action agent executes it via `analyze_image`. Shared memory lets your crew adapt to new visual requirements. You don't hardcode models; the agents decide what to use based on the input data.

Pipeline management for crews

Manage your visual pipelines using `list_pops` and `get_pop` within a hierarchical crew structure. The manager agent monitors the pipeline status, while worker agents use it for detection. This centralized control ensures your vision pipelines remain consistent across the entire crew. You avoid conflicts by letting a single agent manage the pipeline configuration.

Setup guide

Set up EyePop.ai 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 EyePop.ai tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent EyePop.ai 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 →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EyePop.ai. 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 EyePop.ai MCP in CrewAI

Pass the EyePop.ai MCP server URL directly into your agent definition in CrewAI. The agents will automatically register and use the available tools.

Yes. Each agent in your crew can have access to the EyePop.ai tools, allowing them to collaborate on complex visual analysis tasks.

They can. You define a sequential process where one agent analyzes the image and another agent acts on the results provided by the MCP Server.

Use the `tool_filter` in your CrewAI setup. This ensures only the correct agents have the authority to call sensitive tools like `create_pop`.

Video data is processed through the EyePop.ai engine. Your CrewAI agents only receive the detection labels and coordinates, keeping your data footprint small.

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