Brightcove MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Brightcove as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Brightcove. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Brightcove?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Brightcove tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Brightcove MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Brightcove MCP Server
LlamaIndex provides unique advantages when paired with Brightcove through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Brightcove tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Brightcove tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Brightcove, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Brightcove tools were called, what data was returned, and how it influenced the final answer
Brightcove + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Brightcove MCP Server delivers measurable value.
Hybrid search: combine Brightcove real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Brightcove to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Brightcove for fresh data
Analytical workflows: chain Brightcove queries with LlamaIndex's data connectors to build multi-source analytical reports
Brightcove MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Brightcove to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Brightcove to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBrightcove + LlamaIndex FAQ
Common questions about integrating Brightcove MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Brightcove with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Brightcove to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.