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

Q: Can I use Yitu Technology / 依图科技's search tools with LlamaIndex?

Absolutely. You can run searchfaceinrepo and then pass the top results to be indexed by LlamaIndex, allowing users to ask questions like 'Who was found in repo X last month?'

Q: Does the MCP Server support filtering resources for LlamaIndex?

Yes. You can use allowedtools filters and include resource definitions when connecting the Yitu Technology / 依图科技 server, giving your agent precise control over available tools.

Index API results into knowledge bases with Yitu Technology / 依图科技 using LlamaIndex.

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Connect Yitu Technology / 依图科技 MCP to LlamaIndex

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

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Searchable Biometric Records

Don't just process a face; index the findings. After running `search_face_in_repo` and getting top matches, you can index those results into your vector store. Later, you query that knowledge base to ask about past verification outcomes. This means your RAG application doesn't hallucinate—it grounds answers in actual API data from the MCP Server.

Moderation Contextual Search

Use `moderate_image` and then index the moderation report itself. If a user asks, 'What were the policy violations on this image last week?', LlamaIndex retrieves that specific record from your knowledge base. This turns temporary API calls into persistent, searchable corporate knowledge.

Anti-Spoofing Documentation

Whenever `detect_silent_liveness` runs and passes or fails, you can capture that metadata and index it. This builds a historical record of anti-spoofing attempts on certain users or devices. Your knowledge base becomes the source of truth for security audit reports.

Setup guide

Set up Yitu Technology / 依图科技 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Yitu Technology / 依图科技 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Yitu Technology / 依图科技 tools.",
)
response = await agent.run("List recent Yitu Technology / 依图科技 data")

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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 LlamaIndex

It makes your MCP tool output a searchable data source. Instead of the answer disappearing after the session, you index the API results—like face matches or OCR text—into your vector store for later querying.

You can query historical data on facial recognition, content moderation reports, and repository management details. Any result generated by the MCP Server becomes part of your unified index.

Absolutely. You can run `search_face_in_repo` and then pass the top results to be indexed by LlamaIndex, allowing users to ask questions like 'Who was found in repo X last month?'

Yes. You can use `allowed_tools` filters and include resource definitions when connecting the Yitu Technology / 依图科技 server, giving your agent precise control over available tools.

The key indexed data includes biometric matches (1:N), extracted text from documents (`ocr_id_card`), and liveness detection pass/fail records.

Use it with your favorite AI tools

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