Vimeo 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 Vimeo as an MCP tool provider through the 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 Vimeo. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Vimeo?"
)
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 Vimeo MCP Server
Empower your AI agent to orchestrate your entire video ecosystem on Vimeo, the world's most innovative video platform. By connecting Vimeo to your agent, you transform complex asset management into a natural conversation. Your agent can instantly list your videos, audit project folders, and retrieve performance stats without you ever touching a dashboard. Whether you are a professional filmmaker or a corporate communications lead, your agent acts as a real-time video operator, ensuring your content is always organized and accessible.
LlamaIndex agents combine Vimeo tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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 Auditing — List all videos in your account and retrieve detailed metadata, including duration, plays, and privacy settings.
- Folder Oversight — Browse your project folders to maintain a clear view of your content organization.
- Showcase Management — List all showcases (albums) and channels to monitor your public video distribution.
- Video Governance — Update video titles, descriptions, and autonomously delete items when they are no longer needed.
- Search Intelligence — Query public videos across Vimeo to find inspiration or relevant community content.
The Vimeo 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 Vimeo to LlamaIndex via MCP
Follow these steps to integrate the Vimeo 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 Vimeo
Why Use LlamaIndex with the Vimeo MCP Server
LlamaIndex provides unique advantages when paired with Vimeo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Vimeo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Vimeo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Vimeo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Vimeo tools were called, what data was returned, and how it influenced the final answer
Vimeo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Vimeo MCP Server delivers measurable value.
Hybrid search: combine Vimeo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Vimeo 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 Vimeo for fresh data
Analytical workflows: chain Vimeo queries with LlamaIndex's data connectors to build multi-source analytical reports
Vimeo MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Vimeo to LlamaIndex via MCP:
delete_video
Delete a video from Vimeo
get_me
Get authenticated user info from Vimeo
get_video
Get details for a specific video
list_channels
List channels followed by a user
list_folders
List folders (projects) for a user
list_groups
List groups followed by a user
list_showcases
List showcases (albums) for a user
list_videos
List videos for a user
search_videos
Search for public videos on Vimeo
update_video
Update video metadata
Example Prompts for Vimeo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Vimeo immediately.
"List my last 5 videos in Vimeo."
"Show me my Vimeo project folders."
"Search for public videos about 'Artificial Intelligence'."
Troubleshooting Vimeo MCP Server with LlamaIndex
Common issues when connecting Vimeo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpVimeo + LlamaIndex FAQ
Common questions about integrating Vimeo 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 Vimeo 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 Vimeo to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.