How do I validate a Vivo login token from my backend?

Use the `validate_login` tool with the user's token provided by the Vivo SDK. The agent will connect to the Vivo verification server and return the `openid` if the session is legitimate.

Can I automatically query the status of a specific order?

Yes! Use the `query_order` tool with your CP Order ID. Your agent will retrieve the payment status, amount, and internal transaction reference directly from the Vivo gateway.

How do I report character role information to the platform?

Use the `report_role_info` tool with a JSON string containing the character details (name, level, server). This is essential for compliance and social features within the Vivo ecosystem.

Vivo Game Open Platform MCP Server for CrewAI 9 tools — connect in under 2 minutes

Name: Vivo Game Open Platform
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to Vivo Game Open Platform through the Vinkius — pass the Edge URL in the `mcps` parameter and every Vivo Game Open Platform 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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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Vivo Game Open Platform Specialist",
    goal="Help users interact with Vivo Game Open Platform effectively",
    backstory=(
        "You are an expert at leveraging Vivo Game Open Platform 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 Vivo Game Open Platform "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

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

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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 Vivo Game Open Platform MCP Server

Connect your AI agents to the Vivo Game Open Platform (vivo 开放平台), the primary ecosystem for game distribution on Vivo mobile devices. This MCP provides 9 tools to automate server-to-server validation, payment tracking, and player data reporting for high-performance mobile and mini-games.

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

Authentication — Validate user tokens and retrieve unique openid identifiers from the Vivo account service
Payment Orchestration — Query real-time status for payment orders and reconcile transactions programmatically
Game Analytics — Report player progress, high scores, and level data to the Vivo Game Center rankings
Role Management — Update character/role information including names, levels, and server assignments
App Configuration — Fetch current application settings and list active game servers from the developer console

The Vivo Game Open Platform MCP Server exposes 9 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 Vivo Game Open Platform to CrewAI via MCP

Follow these steps to integrate the Vivo Game Open Platform 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 9 tools from Vivo Game Open Platform

Why Use CrewAI with the Vivo Game Open Platform MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Vivo Game Open Platform 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

Vivo Game Open Platform + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Vivo Game Open Platform MCP Server delivers measurable value.

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

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

Vivo Game Open Platform MCP Tools for CrewAI (9)

These 9 tools become available when you connect Vivo Game Open Platform to CrewAI via MCP:

get_app_config

Retrieve application configuration from Vivo platform

get_server_time

Synchronize with Vivo platform server time

get_user_info

Retrieve basic profile data for a Vivo user

list_game_servers

Query the list of game servers

list_items

Query available virtual items for the app

query_order

Check the status of a specific payment order

report_game_data

Submit player progress and scores to Vivo Game Center

report_role_info

Report character or role information

validate_login

Verify a user login token from Vivo SDK

Example Prompts for Vivo Game Open Platform in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Vivo Game Open Platform immediately.

"Check the status of Vivo order ID 'cp_order_555666'."

"Validate the login token 'tok_vivo_abc' from the client."

"List all active game servers configured in the Vivo console."

Troubleshooting Vivo Game Open Platform MCP Server with CrewAI

Common issues when connecting Vivo Game Open Platform 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.

Vivo Game Open Platform + CrewAI FAQ

Common questions about integrating Vivo Game Open Platform 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.