How to Use the Yitu Technology / 依图科技 MCP in OpenAI Agents SDK

Q: Can I extract text from documents using Yitu Technology / 依图科技 with the OpenAI Agents SDK?

Yep. You just use ocridcard to pull clean text data out of an ID card image. Your agent can then take that extracted text and use it for subsequent processing steps.

Run facial recognition and anti-spoofing checks directly from your OpenAI Agents SDK workflow.

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Connect Yitu Technology / 依图科技 MCP to OpenAI Agents SDK

Create your Vinkius account to connect Yitu Technology / 依图科技 to OpenAI Agents SDK 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 OpenAI Agents SDK

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Claude

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Manage Facial Identity Records

You can start by creating a new identity record using `create_face_repo`. This establishes the secure container for storing biometric data. Later, you'll use `add_face_to_repo` to register specific faces into that repository. When cleanup is needed or an identity changes, simply call `delete_face_repo`.

Verify Live Presence & Authenticity

Need to know if the person in the picture is real? Use `detect_active_liveness`, which returns pass/fail metrics for specific actions. This handles live, interactive verification. For anti-spoofing checks on static images or screens, run `detect_silent_liveness`. It's great at catching photos and 3D masks—it’s a solid layer of defense.

Search & Identify People (1:N)

To find someone in your database, you run `search_face_in_repo`. This tool returns top matches along with confidence scores, giving you the best suspects immediately. If you need to check if two specific faces are identical, use `compare_faces` for a direct 1:1 verification. You can also narrow your search scope by listing all available repositories first using `list_repos`.

Setup guide

Set up Yitu Technology / 依图科技 MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Yitu Technology / 依图科技 tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Yitu Technology / 依图科技 tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Yitu Technology / 依图科技 tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Yitu Technology / 依图科技 Agent",
            instructions="You have access to Yitu Technology / 依图科技 tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Yitu Technology / 依图科技 MCP in OpenAI Agents SDK

The MCP Server automatically discovers the tools, letting your agents know exactly what's available. You just pass the server instance to the agent constructor, and it handles the rest for you.

It touches biometric face data and image content when performing operations like `moderate_image`. When designing your workflow, remember that handling this type of sensitive information requires careful guardrails.

Yep. You just use `ocr_id_card` to pull clean text data out of an ID card image. Your agent can then take that extracted text and use it for subsequent processing steps.

The MCP Server handles repository management, letting you create new repositories via `create_face_repo`. While we don't list hard caps here, the platform is built for enterprise scale.

You can remove a specific face from an existing repository by calling `remove_face_from_repo`. This keeps the repo intact but cleans up the unwanted biometric data.

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