How do I get my API Keys for Friendbuy?

Log in to your Friendbuy account, go to Settings > Developer, and you will find your Access Key and Secret Key.

Can I manually log a purchase through the agent?

Yes! Use the 'track_conversion_purchase' tool. Provide the Order ID, amount, and customer email. If you include the 'referralCode', it will trigger the advocate's reward.

How do I verify if a referral code is still valid?

Use the 'get_referral_code_status' tool. The agent will check the Developer API and return the active status and associated reward value.

Is it possible to list webhooks?

Yes, the 'list_webhooks' tool retrieves all active webhook configurations so you can verify where real-time reward notifications are being sent.

Friendbuy MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Friendbuy
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

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

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python

from crewai import Agent, Task, Crew

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

Connect your Friendbuy account to any AI agent to automate your referral programs and customer loyalty workflows through the Model Context Protocol (MCP). Friendbuy is a high-growth referral marketing platform that powers word-of-mouth campaigns for leading brands. This MCP server enables you to track referral events, log conversions, and retrieve reward distributions directly through natural conversation.

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

Key Features

Referral Rewards Tracking — List all distributed referral rewards and filter them by advocate to understand who your top promoters are.
Conversion Logging — Post purchase and signup events programmatically to trigger the referral reward lifecycle.
Code Generation & Verification — Create personal referral codes for customers and check their active statuses instantly.
Purchase History — Retrieve a list of all tracked purchases that have been attributed to referral campaigns.
Webhook Monitoring — List configured webhooks to ensure your internal systems are receiving real-time reward notifications.
API Health Checks — Verify your connection to both the Merchant API and Developer API v2 environments seamlessly.

The Friendbuy 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 Friendbuy to CrewAI via MCP

Follow these steps to integrate the Friendbuy 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 Friendbuy

Why Use CrewAI with the Friendbuy MCP Server

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

Friendbuy + CrewAI Use Cases

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

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

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

Friendbuy MCP Tools for CrewAI (8)

These 8 tools become available when you connect Friendbuy to CrewAI via MCP:

check_api_connection

Verify API access

create_referral_code

Generate share code

get_referral_code_status

Check code status

list_referral_rewards

List awarded referrals

list_tracked_purchases

List tracked purchases

list_webhooks

List webhook configs

track_conversion_purchase

Log a purchase

track_conversion_signup

Log a signup

Example Prompts for Friendbuy in CrewAI

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

"List all recent referral rewards distributed."

"Generate a new referral code for customer 'user_123' (jane@email.com)."

"Track a $50 purchase for order 'ORD-987' from 'friend@email.com' using code 'JANE-REF-99'."

Troubleshooting Friendbuy MCP Server with CrewAI

Common issues when connecting Friendbuy 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.

Friendbuy + CrewAI FAQ

Common questions about integrating Friendbuy 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.