Can I check if a video has been processed and is active?

Yes! Use the `get_video` tool with the Video ID. Your agent will fetch the current state, showing if it is 'ACTIVE', 'INACTIVE', or still being processed.

How do I list all the videos with a specific tag?

Simply ask the agent to `list_videos` and provide a search query like `tags:summer`. It will retrieve all matching media assets from your library.

Does the integration allow creating a new playlist?

Yes. Use the `create_playlist` action and provide a name and type (e.g., EXPLICIT or SMART). You can then organize your videos into this new collection.

Brightcove MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Brightcove
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Brightcove through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Brightcove "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Brightcove?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Brightcove MCP Server

Connect your Brightcove Video Cloud account to any AI agent and orchestrate your video management, publishing, and analytics workflows through natural conversation.

Pydantic AI validates every Brightcove tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Video Oversight — List all videos in your library, search by tags or metadata, and retrieve detailed technical specifications.
Playlist Management — Create, update, and manage playlists to organize your content for different platforms.
Metadata Control — Update video names, descriptions, and states (active/inactive) directly from your workspace.
Content Organization — Access and list folders to verify how your assets are structured.
Library Insights — Retrieve total video counts and monitor the status of individual media assets.

The Brightcove MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Brightcove to Pydantic AI via MCP

Follow these steps to integrate the Brightcove MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Brightcove with type-safe schemas

Why Use Pydantic AI with the Brightcove MCP Server

Pydantic AI provides unique advantages when paired with Brightcove through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Brightcove integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Brightcove connection logic from agent behavior for testable, maintainable code

Brightcove + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Brightcove MCP Server delivers measurable value.

Type-safe data pipelines: query Brightcove with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Brightcove tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Brightcove and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Brightcove responses and write comprehensive agent tests

Brightcove MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Brightcove to Pydantic AI via MCP:

create_playlist

Create a new playlist

delete_video

Delete a video permanently

get_folder_videos

List videos within a specific folder

get_playlist

Get details of a specific playlist

get_video

Get details of a specific video

get_video_count

Get total number of videos in the account

list_folders

List all video folders

list_playlists

List all playlists

list_videos

List all videos in the account

update_video

Update metadata for a video

Example Prompts for Brightcove in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Brightcove immediately.

"List the last 5 videos added to my Brightcove account."

"Show the playlists I have configured."

"Find all videos tagged with 'tutorial'."

Troubleshooting Brightcove MCP Server with Pydantic AI

Common issues when connecting Brightcove to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Brightcove + Pydantic AI FAQ

Common questions about integrating Brightcove MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Brightcove MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.