Can my AI automatically find the details of an assistant just by providing its ID?

Yes! Use the `get_assistant_info` tool with the Assistant ID. Your agent will respond with complete metadata, configuration, and capabilities connected to that specific agent in seconds.

How do I check the remaining token quota for my account?

Simply ask the agent to run the `get_usage` action. It will retrieve the current token consumption statistics and the remaining quota provided by the Yuanqi platform.

Can I upload multiple files for my assistant's knowledge base?

Yes! Use the `upload_file` tool for each document you want to add. After uploading, use the `list_files` tool to verify they are processed and available for RAG operations.

Tencent Yuanqi MCP Server for LangChain 9 tools — connect in under 2 minutes

Name: Tencent Yuanqi
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 9 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Tencent Yuanqi through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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({
        "tencent-yuanqi": {
            "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 Tencent Yuanqi, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Tencent Yuanqi MCP Server

Connect your AI agents to Tencent Yuanqi (腾讯元器), the official intelligent agent platform powered by the Hunyuan large model. This MCP provides 9 tools for comprehensive agent management and high-performance RAG operations.

LangChain's ecosystem of 500+ components combines seamlessly with Tencent Yuanqi through native MCP adapters. Connect 9 tools via the 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

Agent Interaction — Chat with published agents using persistent sessions and context tracking
Document Lifecycle — Upload, list, and delete documents for agent knowledge bases with real-time status tracking
Assistant Profiling — Retrieve metadata and configuration for any assistant in your workspace
Usage Analysis — Monitor token consumption and remaining quota programmatically

The Tencent Yuanqi MCP Server exposes 9 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 Tencent Yuanqi to LangChain via MCP

Follow these steps to integrate the Tencent Yuanqi 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 9 tools from Tencent Yuanqi via MCP

Why Use LangChain with the Tencent Yuanqi MCP Server

LangChain provides unique advantages when paired with Tencent Yuanqi through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine Tencent Yuanqi 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 Tencent Yuanqi queries for multi-turn workflows

Tencent Yuanqi + LangChain Use Cases

Practical scenarios where LangChain combined with the Tencent Yuanqi MCP Server delivers measurable value.

RAG with live data: combine Tencent Yuanqi tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Tencent Yuanqi, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Tencent Yuanqi tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Tencent Yuanqi tool call, measure latency, and optimize your agent's performance

Tencent Yuanqi MCP Tools for LangChain (9)

These 9 tools become available when you connect Tencent Yuanqi to LangChain via MCP:

chat

Requires assistant_id and user_id. Chat with a Tencent Yuanqi assistant

delete_file

Delete an uploaded file

get_assistant_info

Get details about a specific assistant

get_file_info

Get metadata for a specific file

get_file_status

Check file processing status

get_usage

Check API usage and quota

list_assistants

List your own assistants

list_files

List uploaded files

upload_file

) to the Yuanqi platform for use in assistant knowledge bases. Upload a document for assistant context

Example Prompts for Tencent Yuanqi in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Tencent Yuanqi immediately.

"Chat with assistant 'assistant_123' and ask 'Explain the concept of deep learning'."

"Upload the file 'specs.pdf' to my Yuanqi account."

"List all assistants in my account."

Troubleshooting Tencent Yuanqi MCP Server with LangChain

Common issues when connecting Tencent Yuanqi to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Tencent Yuanqi + LangChain FAQ

Common questions about integrating Tencent Yuanqi MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.