How to Use the Yitu Technology / 依图科技 MCP in CrewAI

Q: What kind of identity checks can Yitu Technology / 依图科技 perform with CrewAI?

The team can execute everything from basic detection (detectface) to complex, multi-factor authentication involving both ocridcard and biometric comparisons like comparefaces.

Q: What specific types of media moderation does Yitu Technology / 依图科技 handle with CrewAI?

The platform offers both general content moderation via moderateimage and specialized anti-spoofing checks using detectsilentliveness, covering photos, screens, and masks.

Autonomous identity verification teams using CrewAI and computer vision tools.

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Connect Yitu Technology / 依图科技 MCP to CrewAI

Create your Vinkius account to connect Yitu Technology / 依图科技 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 Yitu Technology / 依图科技 with CrewAI

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Coordinated Identity Verification Teams

You can set up a team where one agent is responsible for data intake, another runs the check, and a third takes action. For example, Agent A uses `detect_face` on an image; Agent B then uses that detected face to run `search_face_in_repo`. The collaboration ensures specialization: Agent C might be assigned only repository maintenance tasks like listing or deleting entries using `list_repos` and `delete_face_repo`.

Multi-Stage Anti-Fraud Screening

A dedicated fraud agent can watch the session while running multiple checks. The first check might be a general content moderation pass via `moderate_image`. If that passes, the second agent runs `detect_silent_liveness` to confirm the input isn't spoofed. The monitor agent watches both outcomes. If either fails, it escalates the task for human review or logs the failure into a centralized record.

Automated Record Management Pipeline

Build a pipeline that keeps your repositories clean and up-to-date. A specialized agent can check existing records using `list_repos` and then verify if certain faces are still active in the system using `compare_faces`. If an identity is confirmed defunct, another agent executes `remove_face_from_repo`, ensuring your stored facial data remains accurate.

Setup guide

Set up Yitu Technology / 依图科技 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 Yitu Technology / 依图科技 tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Yitu Technology / 依图科技 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="Yitu Technology / 依图科技 Analyst",
        goal="Access and analyze Yitu Technology / 依图科技 data via MCP.",
        backstory="Expert analyst with direct Yitu Technology / 依图科技 access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Yitu Technology / 依图科技 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 Yitu Technology / 依图科技. 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 Yitu Technology / 依图科技 MCP in CrewAI

CrewAI specializes in running a team of specialized agents that pass information to each other. Roles are defined, and memory is shared, meaning the output from one agent becomes the input for the next.

The team can execute everything from basic detection (`detect_face`) to complex, multi-factor authentication involving both `ocr_id_card` and biometric comparisons like `compare_faces`.

Yes. You can assign agents to monitor repository health, ensuring that faces are correctly registered (`add_face_to_repo`) and removed when necessary, keeping the system accurate.

The platform offers both general content moderation via `moderate_image` and specialized anti-spoofing checks using `detect_silent_liveness`, covering photos, screens, and masks.

The server handles various forms of sensitive data: biometric facial templates, extracted alphanumeric text from ID cards, and live activity metrics used for liveness verification.

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