Can I list all active rooms on my LiveKit server?

Yes! Use the `list_rooms` tool. It calls the LiveKit RoomService ListRooms endpoint and returns all currently open rooms with their participant count, metadata, and creation time.

How do I mute a participant's microphone?

First use `list_participants` to get the track SID for the participant's audio track. Then call `mute_track` with the room name, participant identity, track SID, and muted set to 'true'.

Does this work with self-hosted LiveKit servers?

Yes! Just provide your self-hosted server's URL (e.g., https://livekit.yourserver.com) as the Host URL, along with the API Key and Secret from your server's config.yaml.

LiveKit Real-Time Rooms MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: LiveKit Real-Time Rooms
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 LiveKit Real-Time Rooms through the 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 LiveKit Real-Time Rooms "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in LiveKit Real-Time Rooms?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 LiveKit Real-Time Rooms MCP Server

Connect your AI agents to LiveKit, the open-source framework and cloud platform for real-time voice, video, and AI agent communication. This MCP provides 10 tools to manage the full room lifecycle via the LiveKit Twirp Room Service API.

Pydantic AI validates every LiveKit Real-Time Rooms tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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

Room Management — Create, list, and delete real-time voice/video rooms with configurable timeouts and participant limits
Participant Control — List, inspect, update metadata, and remove participants from active rooms
Track Moderation — Mute or unmute any published audio/video track for content moderation
Live Data Messaging — Broadcast data payloads to all participants with reliable or lossy delivery modes
Room Metadata — Dynamically update room-level metadata visible to all connected clients

The LiveKit Real-Time Rooms 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 LiveKit Real-Time Rooms to Pydantic AI via MCP

Follow these steps to integrate the LiveKit Real-Time Rooms 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 LiveKit Real-Time Rooms with type-safe schemas

Why Use Pydantic AI with the LiveKit Real-Time Rooms MCP Server

Pydantic AI provides unique advantages when paired with LiveKit Real-Time Rooms 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 LiveKit Real-Time Rooms integration code

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

Dependency injection system cleanly separates your LiveKit Real-Time Rooms connection logic from agent behavior for testable, maintainable code

LiveKit Real-Time Rooms + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the LiveKit Real-Time Rooms MCP Server delivers measurable value.

Type-safe data pipelines: query LiveKit Real-Time Rooms with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple LiveKit Real-Time Rooms tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query LiveKit Real-Time Rooms and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock LiveKit Real-Time Rooms responses and write comprehensive agent tests

LiveKit Real-Time Rooms MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect LiveKit Real-Time Rooms to Pydantic AI via MCP:

create_room

Participants can join it via access tokens. Create a new LiveKit room with specified settings

delete_room

Requires roomCreate permission. Delete a room, disconnecting all participants

get_participant

Get detailed information about a specific participant

list_participants

List all participants currently in a room

list_rooms

List all active rooms on the LiveKit server

mute_track

Mute or unmute a participant's published track

remove_participant

On LiveKit Cloud, their token is also revoked. Remove a participant from a room

send_data

Use "reliable" for guaranteed delivery or "lossy" for low-latency. Send a data message to all participants in a room

update_participant_metadata

Update a participant's metadata

update_room_metadata

Use JSON strings for structured data. Update the metadata of a room

Example Prompts for LiveKit Real-Time Rooms in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with LiveKit Real-Time Rooms immediately.

"List all active rooms on my LiveKit server."

"Create a room called 'interview-session' with a max of 3 participants."

"Remove the participant 'user-abc' from room 'support-call-42'."

Troubleshooting LiveKit Real-Time Rooms MCP Server with Pydantic AI

Common issues when connecting LiveKit Real-Time Rooms to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

LiveKit Real-Time Rooms + Pydantic AI FAQ

Common questions about integrating LiveKit Real-Time Rooms 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 LiveKit Real-Time Rooms MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.