How do I find my Twitch Client ID and Access Token?

Go to the [**Twitch Developer Console**](https://dev.twitch.tv/console), create an App, and generate a Client Secret to get an App Access Token or perform the OAuth flow for a User Token. Copy and paste them below.

Can the agent check if a channel is live?

Yes. Use the `get_streams` tool providing the user login. Your agent will return real-time status, including viewer count and game title if the channel is live.

Is it possible to list top clips via the agent?

Yes. The `get_clips` tool allows your agent to retrieve the most popular clips for a specific broadcaster, helping you identify trending content moments.

Twitch MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Twitch
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Twitch Specialist",
    goal="Help users interact with Twitch effectively",
    backstory=(
        "You are an expert at leveraging Twitch 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 Twitch "
        "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 Twitch MCP Server

Empower your AI agent to orchestrate your entire streaming ecosystem on Twitch, the world's leading live streaming platform. By connecting Twitch to your agent, you transform complex channel management into a natural conversation. Your agent can instantly list live streams, audit your follower base, and retrieve top clips without you ever touching a dashboard. Whether you are a full-time creator or a community manager, your agent acts as a real-time channel coordinator, ensuring your community engagement is always monitored and your content library is organized.

When paired with CrewAI, Twitch becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Twitch 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

Stream Auditing — List live streams by user or game and retrieve real-time viewer counts and statuses.
Community Oversight — Query your follower base, audit channel moderators, and check subscriber details instantly.
Content Management — List all videos and top clips for any broadcaster to stay on top of your highlights.
Channel Intelligence — Retrieve detailed metadata for channels and users to maintain strict organizational control.
Discovery Monitoring — Search for channels and list top games to understand platform trends in real-time.

The Twitch 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 Twitch to CrewAI via MCP

Follow these steps to integrate the Twitch 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 Twitch

Why Use CrewAI with the Twitch MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Twitch 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

Twitch + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Twitch MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Twitch 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 Twitch, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Twitch 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 Twitch against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Twitch MCP Tools for CrewAI (10)

These 10 tools become available when you connect Twitch to CrewAI via MCP:

get_channel_followers

Get followers for a channel

get_channel_info

Get channel information

get_clips

Get clips for a broadcaster

get_followed_channels

Get channels followed by a user

get_streams

Get live streams

get_subscriptions

Get broadcaster subscriptions

get_top_games

Get top games on Twitch

get_users

Get information about Twitch users

get_videos

Get videos for a user

search_channels

Search for Twitch channels

Example Prompts for Twitch in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Twitch immediately.

"Check if user 'ninja' is currently live on Twitch."

"Show me the top 5 games on Twitch right now."

"List the last 5 videos for broadcaster ID 12345."

Troubleshooting Twitch MCP Server with CrewAI

Common issues when connecting Twitch 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.

Twitch + CrewAI FAQ

Common questions about integrating Twitch 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.