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 CrewAI 10 tools — connect in under 2 minutes

Name: LiveKit Real-Time Rooms
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to LiveKit Real-Time Rooms through the Vinkius — pass the Edge URL in the `mcps` parameter and every LiveKit Real-Time Rooms tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="LiveKit Real-Time Rooms Specialist",
    goal="Help users interact with LiveKit Real-Time Rooms effectively",
    backstory=(
        "You are an expert at leveraging LiveKit Real-Time Rooms tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in LiveKit Real-Time Rooms "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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 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.

When paired with CrewAI, LiveKit Real-Time Rooms becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call LiveKit Real-Time Rooms tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the LiveKit Real-Time Rooms MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from LiveKit Real-Time Rooms

Why Use CrewAI with the LiveKit Real-Time Rooms MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with LiveKit Real-Time Rooms through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

LiveKit Real-Time Rooms + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries LiveKit Real-Time Rooms for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries LiveKit Real-Time Rooms, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain LiveKit Real-Time Rooms tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries LiveKit Real-Time Rooms against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

LiveKit Real-Time Rooms MCP Tools for CrewAI (10)

These 10 tools become available when you connect LiveKit Real-Time Rooms to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

LiveKit Real-Time Rooms + CrewAI FAQ

Common questions about integrating LiveKit Real-Time Rooms MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.