How to Use the Kiwify MCP in LlamaIndex

Q: How do I connect the Kiwify MCP Server to LlamaIndex?

Install the MCP tool package with pip. Initialize the BasicMCPClient with the server URL, convert it to tools with McpToolSpec, and pass them to your FunctionAgent.

Q: Can LlamaIndex index my entire Kiwify product catalog?

Yes. The agent uses listproducts to pull the catalog, then parses the details from getproductdetails to build a vector index that your support agents can search semantically.

Q: How does LlamaIndex handle live subscription updates from Kiwify?

You can write a pipeline that queries listactivesubscriptions on a schedule. LlamaIndex upserts these records into your vector database, keeping your customer lifetime value metrics current.

Index your Brazilian ecommerce sales and subscription data directly into LlamaIndex to build queryable, context-rich knowledge bases.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kiwify MCP to LlamaIndex

Create your Vinkius account to connect Kiwify to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Kiwify with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Ground RAG applications in live Kiwify store data

Stop guessing which digital courses are selling. Your agent uses `list_products` to fetch your catalog and indexes the output directly into vector stores for semantic search. When users ask about product availability or pricing, LlamaIndex queries this indexed vector store. It grounds the response in actual catalog data from `get_product_details` instead of relying on outdated training data.

Semantic search with the Kiwify MCP Server

Finding specific customer transaction patterns is painful in raw spreadsheets. The MCP Server lets you pull transaction logs using `list_sales_history` and feed them into your index. You can ask natural language questions about customer trends. The system searches your indexed `list_active_subscriptions` data to identify which cohorts remain active longest.

Real-time webhook indexing for automated knowledge updates

Keep your knowledge base fresh without constant manual rebuilds. The agent calls `create_notification_webhook` to register endpoints that trigger updates whenever a purchase occurs. When the webhook fires, the system fetches details using `get_sale_details` and updates the LlamaIndex document store. This ensures your customer support agent always references the absolute latest transaction state.

Setup guide

Set up Kiwify MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Kiwify MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Kiwify tools.",
)
response = await agent.run("List recent Kiwify data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kiwify. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kiwify now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kiwify MCP in LlamaIndex

Install the MCP tool package with pip. Initialize the `BasicMCPClient` with the server URL, convert it to tools with `McpToolSpec`, and pass them to your `FunctionAgent`.

Yes. The agent uses `list_products` to pull the catalog, then parses the details from `get_product_details` to build a vector index that your support agents can search semantically.

You can write a pipeline that queries `list_active_subscriptions` on a schedule. LlamaIndex upserts these records into your vector database, keeping your customer lifetime value metrics current.

Yes, the framework lets you specify an allowed tools list. If you only want to index catalog data, you can restrict the agent to `list_products` and block access to financial tools.

All transaction details and account summaries retrieved via `get_account_summary` are processed in ephemeral V8 sandboxes. Vinkius handles the authentication token securely, ensuring no raw credentials reach your external database.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript