How to Use the iQiyi Open Platform / 爱奇艺开放平台 MCP in LangChain

Q: How do I handle multi-server setups with iQiyi Open Platform / 爱奇艺开放平台 and LangChain?

Use the LangChain MultiServerMCPClient to connect the iQiyi server alongside other endpoints. This lets your LangChain agent pull user profiles via getuserprofile while querying external databases in the same execution loop.

Q: What is the setup process for this MCP Server in LangChain?

Install the adapter using pip install langchain-mcp-adapters langgraph to prepare your LangChain environment for the iQiyi API. Initialize the client pointing to the Vinkius endpoint, retrieve the tools with client.gettools(), and pass them to your LangChain agent constructor.

Chain iQiyi Open Platform / 爱奇艺开放平台 tools together to build multi-step video search and user profiling pipelines with LangChain.

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Connect iQiyi Open Platform / 爱奇艺开放平台 MCP to LangChain

Create your Vinkius account to connect iQiyi Open Platform / 爱奇艺开放平台 to LangChain 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 iQiyi Open Platform / 爱奇艺开放平台 with LangChain

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Connect LangChain to the iQiyi Open Platform

Feed the output of iQiyi's `search_video_content` directly into `get_content_metadata` using LangChain to construct deep media discovery pipelines. Your LangChain agent can evaluate the returned video search results, pick the top-performing titles, and pull detailed iQiyi metadata in a single run. No manual glue code needed. By coupling the iQiyi Open Platform MCP Server with LangSmith, you trace every tool call to see exactly how your LangChain agent navigates the video catalog. Monitor latency and token usage as your LangChain chain resolves complex user queries on the platform. It is that simple.

Verify VIP Status and Orders in Real Time

Check user accounts by pairing this MCP Server with LangChain to run `get_user_profile` alongside `get_vip_status` to determine subscription tiers instantly. Your LangChain agent can branch its logic based on the retrieved iQiyi membership tier. It serves premium content recommendations or directs free users to billing. Retrieve historical transactions using LangChain with `list_user_orders` and drill down into specific receipts via `get_order_info`. This lets your LangChain pipeline resolve billing questions or verify active iQiyi subscriptions. You protect your premium streams.

Dynamically Map Content Categories and Rankings

Let your LangChain agent query `list_video_categories` to understand the current iQiyi catalog structure before running a search. This prevents the LangChain model from guessing genres. It queries the video platform API with valid parameters every time. Combine these categories with `get_video_rankings` to build automated trend reports via LangChain. The LangChain agent processes the raw ranking data and outputs curated lists of trending iQiyi shows. You get highly targeted recommendations.

Setup guide

Set up iQiyi Open Platform / 爱奇艺开放平台 MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes iQiyi Open Platform / 爱奇艺开放平台 tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "iqiyi-open-platform-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent iQiyi Open Platform / 爱奇艺开放平台 transactions"
    })
    print(result["messages"][-1].content)

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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 iQiyi Open Platform / 爱奇艺开放平台. 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 iQiyi Open Platform / 爱奇艺开放平台 MCP in LangChain

Use the LangChain `MultiServerMCPClient` to connect the iQiyi server alongside other endpoints. This lets your LangChain agent pull user profiles via `get_user_profile` while querying external databases in the same execution loop.

Yes, because the iQiyi tools are exposed via standard LangChain adapters, every call to `search_video_content` or `get_vip_status` is fully visible in your LangSmith dashboard.

The LangChain ReAct agent analyzes the user's prompt and decides if an iQiyi order inquiry fits best. If a user asks about a recent purchase, the LangChain agent first calls `list_user_orders` and then uses the resulting ID to call `get_order_info`.

Install the adapter using `pip install langchain-mcp-adapters langgraph` to prepare your LangChain environment for the iQiyi API. Initialize the client pointing to the Vinkius endpoint, retrieve the tools with `client.get_tools()`, and pass them to your LangChain agent constructor.

Vinkius runs the server in an isolated V8 sandbox, ensuring your iQiyi API credentials and the raw JSON returned by `get_user_profile` are never stored or exposed to external networks. Only the active LangChain session holds this transient data.

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