How do I find my PingPong App ID and Secret?

Log in to the PingPong developer portal or contact your PingPong account manager to receive your unique App ID and App Secret for API integration.

Can I check the balance of my virtual cards (VCC)?

Yes. Use the `get_vcc_balance` tool to retrieve the combined balance of all your virtual card accounts, helping you manage advertising spend or supplier payments.

Is it possible to monitor payout statuses through the agent?

Yes! Use the `get_payout_status` tool with your payout ID to retrieve the current processing status and estimated arrival time for your funds.

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

Name: PingPong
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to PingPong through Vinkius, pass the Edge URL in the `mcps` parameter and every PingPong 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="PingPong Specialist",
    goal="Help users interact with PingPong effectively",
    backstory=(
        "You are an expert at leveraging PingPong 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 PingPong "
        "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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About PingPong MCP Server

Empower your AI agent to orchestrate your cross-border financial operations with PingPong, the leading global payment platform for modern e-commerce. By connecting PingPong to your agent, you transform complex account management and fund orchestration into a natural conversation. Your agent can instantly list your global receiving accounts, retrieve real-time balances, monitor transaction histories, and even initiate payouts without you needing to navigate the complex PingPong dashboard. Whether you are managing multiple Amazon stores or distributing funds to global suppliers, your agent acts as a real-time treasury assistant, keeping your capital accurate and your cross-border payments moving.

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

Account Orchestration — List all your PingPong global receiving accounts and retrieve detailed metadata for each.
Balance Monitoring — Get real-time balance information across multiple currencies and account types.
Transaction Auditing — Browse transaction histories with full support for filtering by status and currency.
Payout Control — Initiate fund withdrawals and monitor the real-time status of your payouts.
Treasury Insights — Retrieve high-level summaries of your global sales and virtual card (VCC) balances.

The PingPong 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 PingPong to CrewAI via MCP

Follow these steps to integrate the PingPong 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 PingPong

Why Use CrewAI with the PingPong MCP Server

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

PingPong + CrewAI Use Cases

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

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

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

PingPong MCP Tools for CrewAI (10)

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

create_payout

Create a new payout

get_account_details

Get account information

get_balance

Get account balance

get_exchange_rates

Get real-time exchange rates

get_payout_status

Check payout status

get_sales_summary

Get global sales summary

get_vcc_balance

Get virtual card balance

list_accounts

List global accounts

list_store_accounts

). List e-commerce store accounts

list_transactions

List account transactions

Example Prompts for PingPong in CrewAI

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

"List all my PingPong receiving accounts."

"What is my current balance in USD across all accounts?"

"Check the status of payout 'PAY-8821'."

Troubleshooting PingPong MCP Server with CrewAI

Common issues when connecting PingPong 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.

PingPong + CrewAI FAQ

Common questions about integrating PingPong 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.