How to Use the Aliyun VOD / 阿里云视频点播 MCP in LlamaIndex

Q: How is my Aliyun VOD / 阿里云视频点播 playback data protected?

All playback URLs and upload credentials fetched via getplaybackinfo or createuploadauth are processed in memory within our secure V8 sandbox. No media assets or token payloads are written to persistent disk on Vinkius.

Index your Aliyun VOD / 阿里云视频点播 video metadata directly into LlamaIndex for semantic search.

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Connect Aliyun VOD / 阿里云视频点播 MCP to LlamaIndex

Create your Vinkius account to connect Aliyun VOD / 阿里云视频点播 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 Aliyun VOD / 阿里云视频点播 with LlamaIndex

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Index Aliyun VOD / 阿里云视频点播 into LlamaIndex

This MCP Server lets LlamaIndex extract video details using `list_media` and `get_media_metadata`. The framework indexes this data into your vector store, turning your video catalog into a queryable knowledge base. Instead of searching by exact titles, users can query their video library semantically. The agent queries the index, retrieves the correct video ID, and calls `get_playback_info` to hand back the stream.

Map video categories to your semantic index

The agent pulls your full media structure using `list_categories`. It then aligns your Aliyun VOD taxonomy with your document indexes, allowing structured filtering during RAG queries. When a user asks for training videos, the agent uses this category map to narrow down the search query space before executing `search_vod_media` to find the exact files.

Fetch live stream URLs during query resolution

When resolving a user query about a specific tutorial, the LlamaIndex agent does not just point to a document. It invokes `get_playback_info` to pull the active streaming URLs directly from Aliyun VOD. Instead of managing static links, this MCP integration gets live URLs on demand so your users never hit expired playback endpoints.

Setup guide

Set up Aliyun VOD / 阿里云视频点播 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 Aliyun VOD / 阿里云视频点播 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 Aliyun VOD / 阿里云视频点播 tools.",
)
response = await agent.run("List recent Aliyun VOD / 阿里云视频点播 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 Aliyun VOD / 阿里云视频点播. 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 Aliyun VOD / 阿里云视频点播 MCP in LlamaIndex

Use llama-index-tools-mcp to connect to the server. The agent can then call `list_media` to fetch your video records and write them directly into your vector index.

Yes. The agent translates user questions into structured queries, executing `search_vod_media` to find matching videos based on the index's findings.

Instantiate the BasicMCPClient with the Vinkius endpoint, convert it via McpToolSpec, and pass the tools to your LlamaIndex FunctionAgent.

The MCP client detects authentication errors during upload steps and runs `refresh_upload_auth` to fetch a new token, keeping the indexing pipeline running.

All playback URLs and upload credentials fetched via `get_playback_info` or `create_upload_auth` are processed in memory within our secure V8 sandbox. No media assets or token payloads are written to persistent disk on Vinkius.

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