How do I find my Tencent Cloud SecretId and SecretKey?

Log in to the [Tencent Cloud Console](https://console.cloud.tencent.com/), navigate to [Access Management] -> [API Key Management] to find or generate your unique SecretId and SecretKey.

A FileId is the unique identifier for a media file in the Tencent Cloud VOD system. It is assigned when a video is uploaded and is used for all media-specific operations like metadata retrieval or deletion.

Does this server support SubAppIds?

Yes! You can provide a `tencent_vod_subappid` in your credentials. If set, the agent will automatically include it in all VOD requests to manage resources within that specific sub-application.

Tencent Cloud VOD / 腾讯云点播 MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Tencent Cloud VOD / 腾讯云点播
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Tencent Cloud VOD / 腾讯云点播 through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Tencent Cloud VOD / 腾讯云点播 "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Tencent Cloud VOD / 腾讯云点播?"
    )
    print(result.data)

asyncio.run(main())

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About Tencent Cloud VOD / 腾讯云点播 MCP Server

Empower your AI agent to orchestrate your video-on-demand infrastructure and digital asset management with Tencent Cloud VOD (云点播), the dominant video processing platform in China. By connecting Tencent VOD to your agent, you transform complex media management, background task tracking, and storage auditing into a natural conversation. Your agent can instantly retrieve detailed video metadata, update media titles and descriptions, search through massive media libraries, and monitor processing tasks without you ever needing to navigate the comprehensive Tencent Cloud Console. Whether you are conducting a digital media audit or coordinating a content distribution refresh, your agent acts as a real-time VOD operations assistant, providing accurate results from a single, authorized source.

Pydantic AI validates every Tencent Cloud VOD / 腾讯云点播 tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Media Orchestration — Retrieve metadata for multiple FileIds, update media info, and delete obsolete assets.
Content Discovery — Search for media files using keywords, classes, and tags with advanced sorting.
Task Auditing — Track the real-time status and technical details of asynchronous VOD background tasks.
Storage Monitoring — Access comprehensive storage volume statistics for specific time ranges.
Classification Management — Retrieve and audit the complete media classification tree for your project.

The Tencent Cloud VOD / 腾讯云点播 MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI 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 Cloud VOD / 腾讯云点播 to Pydantic AI via MCP

Follow these steps to integrate the Tencent Cloud VOD / 腾讯云点播 MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Tencent Cloud VOD / 腾讯云点播 with type-safe schemas

Why Use Pydantic AI with the Tencent Cloud VOD / 腾讯云点播 MCP Server

Pydantic AI provides unique advantages when paired with Tencent Cloud VOD / 腾讯云点播 through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Tencent Cloud VOD / 腾讯云点播 integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Tencent Cloud VOD / 腾讯云点播 connection logic from agent behavior for testable, maintainable code

Tencent Cloud VOD / 腾讯云点播 + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Tencent Cloud VOD / 腾讯云点播 MCP Server delivers measurable value.

Type-safe data pipelines: query Tencent Cloud VOD / 腾讯云点播 with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Tencent Cloud VOD / 腾讯云点播 tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Tencent Cloud VOD / 腾讯云点播 and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Tencent Cloud VOD / 腾讯云点播 responses and write comprehensive agent tests

Tencent Cloud VOD / 腾讯云点播 MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Tencent Cloud VOD / 腾讯云点播 to Pydantic AI via MCP:

delete_media_file

Remove media from VOD

get_media_info

Get video metadata

get_storage_stats

Get storage usage data

get_task_detail

Track VOD task

list_media_classes

List all media classes

list_recent_media

List recently updated media

search_media_files

Search VOD library

update_media_info

Modify media properties

Example Prompts for Tencent Cloud VOD / 腾讯云点播 in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Tencent Cloud VOD / 腾讯云点播 immediately.

"Search for media files containing 'Product Launch' in my VOD library."

"Check the status of VOD task 'task-1234567890'."

"Show me our VOD storage usage stats for the last 30 days."

Troubleshooting Tencent Cloud VOD / 腾讯云点播 MCP Server with Pydantic AI

Common issues when connecting Tencent Cloud VOD / 腾讯云点播 to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Tencent Cloud VOD / 腾讯云点播 + Pydantic AI FAQ

Common questions about integrating Tencent Cloud VOD / 腾讯云点播 MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Tencent Cloud VOD / 腾讯云点播 MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.