How to Use the Wistia MCP in Pydantic AI

Q: How do I get viewer stats with Wistia and Pydantic AI?

You use getengagementstatistics to pull detailed viewership data. This gives you the raw metrics needed for video performance analysis.

Q: What is the process for uploading a new video via Pydantic AI and Wistia?

Use uploadvideoviaurl. You just need to provide the source URL, pick a target project ID, and give it a name. The server handles the entire download and hosting sequence.

Q: How do I check the contents of a Wistia project using Pydantic AI?

Run getprojectdetails. This function pulls all details for a specific folder, including a list of every media asset inside it.

Manage Wistia video assets and analytics with Pydantic AI type safety.

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Connect Wistia MCP to Pydantic AI

Create your Vinkius account to connect Wistia 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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Setup Wistia with Pydantic AI

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Media Asset Metadata Management

`update_media_metadata` lets you programmatically change a media asset's attributes. You need the hashed ID and a JSON object of new data, ensuring your updates are strictly typed. If you want to know what content is available, `list_wistia_medias` gives you every video or audio file in Wistia.

Project Lifecycle Control

`create_new_project` lets you establish a new folder structure for your media. This keeps related assets grouped and organized within Wistia. Conversely, `delete_wistia_project` removes the entire project and all its contents. Since this is irreversible, always confirm before running it.

Retrieving Detailed Project Info

`get_project_details` fetches all details for a specific Wistia folder, listing every media asset contained within it. This is great for audits. You can also check on individual files with `get_media_details`, which retrieves all the comprehensive metadata attached to one asset.

Setup guide

Set up Wistia MCP in Pydantic AI

Prerequisites

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

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

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

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": {
        "wistia-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Wistia MCP in Pydantic AI

You use `get_engagement_statistics` to pull detailed viewership data. This gives you the raw metrics needed for video performance analysis.

Use `upload_video_via_url`. You just need to provide the source URL, pick a target project ID, and give it a name. The server handles the entire download and hosting sequence.

The server interacts with media assets and projects' metadata. Specifically, you are managing attributes like names and descriptions using `update_media_metadata`.

Run `get_project_details`. This function pulls all details for a specific folder, including a list of every media asset inside it.

You receive a complete listing of all the projects (folders) that currently exist within your Wistia account.

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