100ms MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add 100ms 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 100ms. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in 100ms?"
)
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 100ms MCP Server
Connect your 100ms account to any AI agent and manage your live video infrastructure through natural conversation.
LlamaIndex agents combine 100ms tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- Room Management — List all virtual rooms, retrieve deep technical metadata, and create new rooms with specific templates and descriptions
- Session Monitoring — Monitor active or completed video sessions in real-time and retrieve session history across your organization
- Participant Governance — List all peers (participants) currently in a session and retrieve their unique IDs and roles
- Peer Control — Remotely remove or kick participants from active sessions with custom reasons directly from your agent
- Recording Discovery — List and browse cloud recordings, filtered by room or status (completed, failed, or processing)
- Operational Insights — Quickly find unique room, session, and peer IDs required for automated video workflows
- Scalable Infrastructure — Verify your live video configurations and template settings through automated metadata retrieval
The 100ms MCP Server exposes 9 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 100ms to LlamaIndex via MCP
Follow these steps to integrate the 100ms 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 9 tools from 100ms
Why Use LlamaIndex with the 100ms MCP Server
LlamaIndex provides unique advantages when paired with 100ms through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine 100ms tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain 100ms tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query 100ms, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what 100ms tools were called, what data was returned, and how it influenced the final answer
100ms + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the 100ms MCP Server delivers measurable value.
Hybrid search: combine 100ms real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query 100ms 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 100ms for fresh data
Analytical workflows: chain 100ms queries with LlamaIndex's data connectors to build multi-source analytical reports
100ms MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect 100ms to LlamaIndex via MCP:
create_room
Use this when the user asks to start or host a new meeting space. Create a new video room
get_room
Requires the unique room ID. Get the configuration and details of a specific video room
get_session
Get the details and metadata of a specific video session
list_peers
Requires the session ID. List all participants currently inside an active video session
list_recordings
Can optionally filter by room ID or the status of the recording. List cloud recordings of video rooms
list_rooms
Use this to find a room ID. List all video rooms in the 100ms account
list_sessions
You can filter by room ID or status. Use this to find who attended past meetings. List active or past video sessions
remove_peer
Requires the session ID and the peer ID. Kick or remove a specific participant from an active video session
update_room
Requires the room ID. Update the settings of an existing video room
Example Prompts for 100ms in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with 100ms immediately.
"List all my video rooms in 100ms."
"Are there any active sessions for the 'Town Hall' room right now?"
"Remove participant 'peer-123' from the session 'sess-abc' for 'violating community guidelines'."
Troubleshooting 100ms MCP Server with LlamaIndex
Common issues when connecting 100ms to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcp100ms + LlamaIndex FAQ
Common questions about integrating 100ms 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 100ms 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 100ms to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.