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

Q: How do I convert iQiyi Open Platform / 爱奇艺开放平台 tools into LlamaIndex tools?

Use McpToolSpec from llama-index-tools-mcp to wrap the server connection. Calling totoollistasync() automatically converts endpoints like searchvideocontent into schema-compliant tools for your LlamaIndex agent.

Q: Can I filter which iQiyi Open Platform / 爱奇艺开放平台 tools are exposed to LlamaIndex?

Yes, you can use the allowedtools filter when initializing the client. If you only want to allow content discovery, you can expose searchvideocontent and block sensitive tools like getorderinfo in your LlamaIndex setup.

Q: What is the setup command for this MCP Server in LlamaIndex?

Run pip install llama-index-tools-mcp to prepare your LlamaIndex environment for the iQiyi API. Connect to the Vinkius endpoint using BasicMCPClient, wrap it in the tool spec, and pass the tools to your LlamaIndex FunctionAgent.

Q: How secure is my billing and order data when processed by LlamaIndex?

Transactions retrieved via getorderinfo are processed entirely in memory or stored in your private LlamaIndex vector database. The Vinkius sandbox ensures that sensitive financial data from your iQiyi orders never leaves your secure execution environment.

Index iQiyi Open Platform / 爱奇艺开放平台 data directly into your LlamaIndex vector store for grounded RAG applications.

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

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

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Index iQiyi Open Platform Data with this MCP Server

Turn live iQiyi video metadata into indexable documents using LlamaIndex. By calling `get_content_metadata` and `list_video_categories`, your LlamaIndex pipeline can ingest raw platform data, vectorize it, and store it in a local vector database for semantic search. Hallucinations stop here. Instead of relying on frozen model weights, your LlamaIndex agent searches the local vector index populated with fresh content directly from the iQiyi API.

Ground User Profile Queries in Live API Data

Retrieve user metrics using LlamaIndex to query `get_user_profile` and `get_vip_status` to personalize the indexing process. LlamaIndex uses this real-time context to filter search results. This prevents free users from getting premium iQiyi recommendations they cannot watch. The LlamaIndex model queries the active VIP status and matches it against the content categories retrieved by `list_video_categories`. This creates a highly personalized, queryable index of accessible iQiyi media.

Analyze Purchasing History via RAG

Feed transactional data from `list_user_orders` and `get_order_info` directly into your LlamaIndex query engine. This lets users ask natural language questions about their iQiyi spending habits or subscription renewal dates. LlamaIndex structures these iQiyi order details into index nodes. This makes it easy to run complex temporal queries over past purchases without writing SQL or custom parser scripts.

Setup guide

Set up iQiyi Open Platform / 爱奇艺开放平台 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 iQiyi Open Platform / 爱奇艺开放平台 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 iQiyi Open Platform / 爱奇艺开放平台 tools.",
)
response = await agent.run("List recent iQiyi Open Platform / 爱奇艺开放平台 data")

Get your connection token →

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 LlamaIndex

Use `McpToolSpec` from `llama-index-tools-mcp` to wrap the server connection. Calling `to_tool_list_async()` automatically converts endpoints like `search_video_content` into schema-compliant tools for your LlamaIndex agent.

Yes, you can use the `allowed_tools` filter when initializing the client. If you only want to allow content discovery, you can expose `search_video_content` and block sensitive tools like `get_order_info` in your LlamaIndex setup.

The LlamaIndex framework manages tool execution sequentially within the agent loop. For heavy indexing tasks involving `get_content_metadata`, you should implement local debouncers or batching to respect iQiyi's API limits.

Run `pip install llama-index-tools-mcp` to prepare your LlamaIndex environment for the iQiyi API. Connect to the Vinkius endpoint using `BasicMCPClient`, wrap it in the tool spec, and pass the tools to your LlamaIndex `FunctionAgent`.

Transactions retrieved via `get_order_info` are processed entirely in memory or stored in your private LlamaIndex vector database. The Vinkius sandbox ensures that sensitive financial data from your iQiyi orders never leaves your secure execution environment.

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