How to Use the Wistia MCP in Pydantic AI

Q: How do I check all my projects with Wistia and Pydantic AI?

The agent calls listprojects. It returns a list where every field is validated against your defined schema. You get clean, predictable data structure every time.

Q: What analytics can I pull for my videos using Wistia and Pydantic AI?

You retrieve specific performance metrics with getvideostats or overall account stats using getaccountanalytics. The validation layer makes sure these metrics are structured correctly for your downstream processes.

Q: Can I safely update video details using Wistia and Pydantic AI?

Yes. Using updatevideodetails guarantees that the metadata you send back to Wistia adheres strictly to established types. It prevents accidental data corruption, which is critical for production agents.

Q: What's the best way to get a full inventory of media assets with Wistia and Pydantic AI?

Use listvideos. This function pulls all media records, giving you a fully validated list that your agents can iterate over for bulk actions or analysis.

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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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Validate and retrieve account statistics

The agent pulls overall site metrics with `get_account_analytics`. Because of the type-safe approach, if Wistia sends bad data—like a null value where it shouldn't be—the agent fails loudly. No silent corruption. This makes building production agents around the MCP Server much safer.

Manage and validate project metadata

Need to start something new? The agent uses `create_project` and validates the output against your schema. It also lets you list projects with `list_projects`. You can always pull detailed records using `get_project_details`. The type safety ensures that every piece of project metadata you handle is perfectly formed.

Modify video assets and captions reliably

If you need to update a video's description, the agent calls `update_video_details`, guaranteeing the input schema matches what Wistia expects. If it fails validation, your workflow stops—which is exactly what you want. It also handles content details by listing captions using `list_video_captions` and getting general asset info via `get_video_details`.

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-alternative-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

The agent calls `list_projects`. It returns a list where every field is validated against your defined schema. You get clean, predictable data structure every time.

You retrieve specific performance metrics with `get_video_stats` or overall account stats using `get_account_analytics`. The validation layer makes sure these metrics are structured correctly for your downstream processes.

Yes. Using `update_video_details` guarantees that the metadata you send back to Wistia adheres strictly to established types. It prevents accidental data corruption, which is critical for production agents.

Use `list_videos`. This function pulls all media records, giving you a fully validated list that your agents can iterate over for bulk actions or analysis.

The server handles video metadata, project details, account analytics, and video performance statistics. All data types are validated to ensure structural correctness before your agent uses them.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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