How to Use the Brightcove MCP in Pydantic AI

Q: Is the legacy MCPServerHTTP class still supported?

No, MCPServerHTTP is deprecated in the latest versions of the framework. You must use the unified MCPToolset class instead. This provides a cleaner API and better support for external servers.

Build type-safe video workflows using the Brightcove MCP Server with Pydantic AI to validate every API payload.

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Connect Brightcove MCP to Pydantic AI

Create your Vinkius account to connect Brightcove 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 Brightcove with Pydantic AI

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Type-safe Brightcove tool integration with Pydantic AI

The `get_video` and `list_playlists` tools in this Brightcove MCP Server integrate with your agent using type-safe validation to prevent payload corruption. You initialize the connection using `MCPToolset` pointing to the Vinkius HTTP endpoint. The server exposes these data streams directly to your Python runtime. If the server returns unexpected video metadata, Pydantic AI validates it immediately, catching schema mismatches before they break your application.

Runtime validation for playlist creation

The `create_playlist` tool lets you build new playlists with strict parameter validation. When your agent generates a playlist payload, the framework checks the structure against defined schemas. If the model hallucinates a field or sends an invalid format, the system fails loudly. You avoid sending broken API requests to your video cloud, keeping your production data clean.

Safe video metadata updates

The `update_video` tool allows your agent to modify video details with complete runtime safety. Your schema definitions ensure that fields like tags, descriptions, and custom fields match your exact data models. This strict validation prevents silent failures where models write bad data to your production assets. You get predictable, typed execution every time your agent updates a video.

Setup guide

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

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

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

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Common questions about Brightcove MCP in Pydantic AI

You instantiate the MCP toolset with the HTTP URL provided by Vinkius. Pass this toolset into the `toolsets` argument when initializing your Pydantic AI agent. The framework automatically registers the ten video management tools.

The framework will immediately raise a validation error and fail loudly. This prevents your agent from processing corrupt or hallucinated data. You can catch these errors in your application code to handle them safely.

Yes, the toolset supports both Streamable HTTP and SSE transports. You simply pass the correct endpoint URL to your toolset configuration. This ensures reliable real-time communication with your video library.

No, `MCPServerHTTP` is deprecated in the latest versions of the framework. You must use the unified `MCPToolset` class instead. This provides a cleaner API and better support for external servers.

Your credentials and video details are isolated inside a dedicated V8 sandbox on Vinkius. Pydantic AI only receives validated JSON payloads from the server. No raw account credentials or playlist structures are stored or exposed to external models.

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