How to Use the Gumlet MCP in Pydantic AI

Q: Can I use Pydantic AI to delete videos safely using Gumlet?

Yes. The agent can call deletevideo to remove assets. Because the parameters are strictly validated, you do not have to worry about the agent passing malformed IDs to the API.

Enforce strict runtime type safety over your Gumlet video uploads and analytics using Pydantic AI and this MCP Server.

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Connect Gumlet MCP to Pydantic AI

Create your Vinkius account to connect Gumlet 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 Gumlet with Pydantic AI

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Strict schema validation with Pydantic AI

Avoid silent API failures during media ingestion. By loading this MCP Server into your agent, every response from Gumlet is validated against strict Pydantic schemas before your application logic runs. When your agent queries asset details with `get_video_details`, any unexpected API changes trigger immediate, loud validation errors. This keeps your production pipelines safe from corrupted metadata.

Type-safe video analytics reporting

Build reliable reporting workflows that never break due to unexpected null values. The agent pulls viewing statistics using `get_video_analytics` and parses the payload through strict type definitions. You can combine this with `list_video_collections` to generate structured reports. If the API returns unexpected data types, the framework stops execution before bad data pollutes your database.

Secure media folder management

Let your agent manage folders and file uploads without worrying about input validation bugs. The agent uses `create_collection` to set up directories and verifies the output matches your exact model schemas. It can list active sources with `list_image_sources` to ensure your CDN configurations are correct. This gives you a type-safe way to monitor your media assets at runtime.

Setup guide

Set up Gumlet 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": {
        "gumlet-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Gumlet MCP in Pydantic AI

Initialize MCPToolset with the server URL and pass it to the Agent constructor in the toolsets list. The agent will dynamically register all 12 media tools.

Pydantic AI will raise a validation error instantly. This prevents your agent from working with corrupted video metadata or hallucinating fields that do not exist in the API response.

Yes. The agent can call `delete_video` to remove assets. Because the parameters are strictly validated, you do not have to worry about the agent passing malformed IDs to the API.

Yes. The toolset supports both Streamable HTTP and SSE transports, allowing you to connect to the server depending on how your infrastructure is set up.

Your credentials stay local to your environment variables. The server processes requests in a secure V8 sandbox, meaning your video files, user lists, and keys are never exposed to external logs.

Use it with your favorite AI tools

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