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How to Use the Vidyard MCP in Pydantic AI

Manage Vidyard hosting using the Pydantic AI framework for guaranteed correctness.

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Pydantic AI

Connect Vidyard MCP to Pydantic AI

Create your Vinkius account to connect Vidyard to Pydantic AI 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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Controlled Player Updates with MCP Server

The agent can manage player containers by listing them all via `list_video_players`. It also lets you set a new display title using `update_player_name`, ensuring that the data type matches expectations. This high degree of type safety means your logic won't break when changing video player titles.

Getting Specific Video Details

You can pull technical metadata on a video asset using `get_video_details`. If you need the direct links for multiple stream qualities (like 720p), use `get_video_source_files`. These tools allow your Pydantic AI agent to validate that all necessary inputs and outputs are correct before proceeding.

Full Asset Lifecycle Control

Need to add a video? Call `attach_video_to_player` with the two required IDs. Need cleanup? Use `delete_video_asset` or `delete_video_player`. The ability to call these functions makes your agent robust and predictable. It's great knowing that even destructive actions are handled through validated tool calls.

Setup guide

Set up Vidyard MCP in Pydantic AI

Prerequisites

  • Python 3.10+ installed
  • pydantic-ai-slim[fastmcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install Pydantic AI with FastMCP

    Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.

  2. 2

    Configure the FastMCPToolset

    Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.

  3. 3

    Create and run your agent

    Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "vidyard-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Vidyard tools.",
)

result = await agent.run("List recent Vidyard transactions")
print(result.output)

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Why Choose Vinkius

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Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Vidyard MCP in Pydantic AI

You run `list_videos` to get a structured list of every asset in your dashboard. Since everything is validated, you know exactly what data fields you're working with.
The toolset provides `create_empty_player` to build a new container. You can check its current status anytime using `get_player_details`, ensuring the data model is correct.
Yes, use `delete_video_asset`. Since your agent relies on validated types, it handles the necessary parameters to make sure this irreversible action is performed correctly.
Of course. `update_player_name` lets you modify the display title of a video player, guaranteeing that the new string adheres to the expected format.
This server manages two primary types: structured player configuration records and technical metadata associated with video assets.

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