Yitu Technology / 依图科技 MCP Server for LangChain 12 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Yitu Technology / 依图科技 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"yitu-technology": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Yitu Technology / 依图科技, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Yitu Technology / 依图科技 MCP Server
Empower your AI agent to orchestrate your enterprise-grade visual intelligence and facial recognition workflows with Yitu Technology (依图科技), a world-class provider of computer vision solutions. By connecting Yitu to your agent, you transform complex facial matching, identity search, and repository management into a natural conversation. Your agent can instantly detect faces in images, verify identities through high-precision comparison, manage custom facial repositories, and index new identities without you ever needing to navigate complex technical dashboards. Whether you are building an automated security checkpoint or managing a high-volume digital identity archive, your agent acts as a real-time computer vision coordinator, providing accurate results from a single, authorized source.
LangChain's ecosystem of 500+ components combines seamlessly with Yitu Technology / 依图科技 through native MCP adapters. Connect 12 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Facial Orchestration — Detect faces and extract precise locations and attributes from image URLs.
- Identity Verification — Perform high-precision 1:1 face comparison to verify if two images belong to the same person.
- Library Search — Search for matching identities within your private facial repositories (1:N recognition).
- Repository Management — Create, list, and monitor metadata for your facial data repositories.
- Identity Indexing — Register new faces and associate them with unique person identifiers for future search.
The Yitu Technology / 依图科技 MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Yitu Technology / 依图科技 to LangChain via MCP
Follow these steps to integrate the Yitu Technology / 依图科技 MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 12 tools from Yitu Technology / 依图科技 via MCP
Why Use LangChain with the Yitu Technology / 依图科技 MCP Server
LangChain provides unique advantages when paired with Yitu Technology / 依图科技 through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Yitu Technology / 依图科技 MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Yitu Technology / 依图科技 queries for multi-turn workflows
Yitu Technology / 依图科技 + LangChain Use Cases
Practical scenarios where LangChain combined with the Yitu Technology / 依图科技 MCP Server delivers measurable value.
RAG with live data: combine Yitu Technology / 依图科技 tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Yitu Technology / 依图科技, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Yitu Technology / 依图科技 tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Yitu Technology / 依图科技 tool call, measure latency, and optimize your agent's performance
Yitu Technology / 依图科技 MCP Tools for LangChain (12)
These 12 tools become available when you connect Yitu Technology / 依图科技 to LangChain via MCP:
add_face_to_repo
Register a face in a repository
compare_faces
Verify if two faces match (1:1)
create_face_repo
Create a new facial repository
delete_face_repo
Delete a facial repository
detect_active_liveness
Returns per-action pass/fail. Active liveness detection with action verification
detect_face
Detect faces in an image
detect_silent_liveness
Detects photos, screens, and 3D masks. Silent liveness detection (anti-spoofing)
list_repos
List all facial repositories
moderate_image
Content moderation for images
ocr_id_card
Extract text from an ID card image
remove_face_from_repo
Remove a face from a repository
search_face_in_repo
Returns top matches with confidence. Search for a face in a repository (1:N)
Example Prompts for Yitu Technology / 依图科技 in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Yitu Technology / 依图科技 immediately.
"Detect faces in this URL: [URL] and tell me how many people are there."
"Search for this face: [URL] in repository 'REPO_8821'."
"List all facial repositories in my Yitu project."
Troubleshooting Yitu Technology / 依图科技 MCP Server with LangChain
Common issues when connecting Yitu Technology / 依图科技 to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersYitu Technology / 依图科技 + LangChain FAQ
Common questions about integrating Yitu Technology / 依图科技 MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Yitu Technology / 依图科技 with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Yitu Technology / 依图科技 to LangChain
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.