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 LlamaIndex 8 tools — connect in under 2 minutes

Name: Friendbuy
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Friendbuy as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Friendbuy. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Friendbuy?"
    )
    print(response)

asyncio.run(main())

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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.

LlamaIndex agents combine Friendbuy tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Friendbuy MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Friendbuy

Why Use LlamaIndex with the Friendbuy MCP Server

LlamaIndex provides unique advantages when paired with Friendbuy through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Friendbuy tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Friendbuy tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Friendbuy, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Friendbuy tools were called, what data was returned, and how it influenced the final answer

Friendbuy + LlamaIndex Use Cases

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

Hybrid search: combine Friendbuy real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Friendbuy to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Friendbuy for fresh data

Analytical workflows: chain Friendbuy queries with LlamaIndex's data connectors to build multi-source analytical reports

Friendbuy MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Friendbuy to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

Common issues when connecting Friendbuy to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Friendbuy + LlamaIndex FAQ

Common questions about integrating Friendbuy MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Friendbuy tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.