How do I find my ZEGO AppID and ServerSecret?

Log in to the [ZEGO Admin Console](https://console.zego.im/), create or select a project, and you will find your AppID and ServerSecret in the project configuration or basic information section.

What is the SignatureNonce used for?

The SignatureNonce is a random string used to prevent replay attacks. This server automatically generates a fresh nonce for every request to ensure high security for your RTC management.

Can I kick a user from a specific room?

Yes! Use the `kick_room_user` tool with the target RoomId and UserId. You can also provide a custom message that the user will see when they are disconnected.

ZEGO / 即构科技 MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: ZEGO / 即构科技
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to ZEGO / 即构科技 through Vinkius, pass the Edge URL in the `mcps` parameter and every ZEGO / 即构科技 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="ZEGO / 即构科技 Specialist",
    goal="Help users interact with ZEGO / 即构科技 effectively",
    backstory=(
        "You are an expert at leveraging ZEGO / 即构科技 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 ZEGO / 即构科技 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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High SecurityEnterprise-grade

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DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

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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 ZEGO / 即构科技 MCP Server

Empower your AI agent to orchestrate your real-time communication infrastructure with ZEGO (即构科技), the premier provider of global video and audio RTC services. By connecting ZEGO to your agent, you transform complex room management, stream control, and user status tracking into a natural conversation. Your agent can instantly retrieve active room lists, monitor user counts, force-stop media streams, and audit service usage statistics without you ever needing to navigate multiple technical dashboards. Whether you are building an automated moderation system for live rooms or monitoring cross-regional connectivity, your agent acts as a real-time RTC operations assistant, providing accurate and reliable results from a single, authorized source.

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

What you can do

Room Orchestration — List active rooms, retrieve detailed metadata, and monitor real-time user activity.
User Management — Track user status (online/offline), list members in specific rooms, and manage access (kick users).
Stream Control — Monitor active media streams and force-terminate unauthorized or problematic broadcasts.
Usage Auditing — Retrieve comprehensive audio and video duration statistics for specific time ranges.
Operational Insights — Monitor total online user counts and API connectivity status to ensure system-wide health.

The ZEGO / 即构科技 MCP Server exposes 8 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 ZEGO / 即构科技 to CrewAI via MCP

Follow these steps to integrate the ZEGO / 即构科技 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 8 tools from ZEGO / 即构科技

Why Use CrewAI with the ZEGO / 即构科技 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with ZEGO / 即构科技 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 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

ZEGO / 即构科技 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the ZEGO / 即构科技 MCP Server delivers measurable value.

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

Multi-source enrichment pipelines: chain ZEGO / 即构科技 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 ZEGO / 即构科技 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

ZEGO / 即构科技 MCP Tools for CrewAI (8)

These 8 tools become available when you connect ZEGO / 即构科技 to CrewAI via MCP:

check_user_status

Check status of multiple users

get_online_count

Get total online user count

get_room_streams

List active streams in a room

get_room_users

List users in a room

get_usage_stats

Get service usage statistics

kick_room_user

Kick user from room

list_rooms

List active rooms

stop_media_stream

Force stop a stream

Example Prompts for ZEGO / 即构科技 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with ZEGO / 即构科技 immediately.

"List all active rooms in our ZEGO project."

"Check the status for these users: 'user_01,user_02'."

"What is our video usage duration for the last 7 days?"

Troubleshooting ZEGO / 即构科技 MCP Server with CrewAI

Common issues when connecting ZEGO / 即构科技 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

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

ZEGO / 即构科技 + CrewAI FAQ

Common questions about integrating ZEGO / 即构科技 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.