How to Use the GrowingIO MCP in LlamaIndex

Q: How do I index GrowingIO analytics data using LlamaIndex?

Install llama-index-tools-mcp and initialize the MCP client. Convert the tools to a list of executable specifications and pass them to your LlamaIndex agent to start indexing your metrics.

Q: Can LlamaIndex query historical GrowingIO segment data?

Yes, your LlamaIndex agent can call listsegments to retrieve active groups. It then indexes these definitions so you can run semantic searches over your user cohorts.

Q: Does LlamaIndex support real-time event tracking with GrowingIO?

Yes, the LlamaIndex agent can call getevent on demand to fetch live event metadata. This ensures your knowledge base stays updated with the latest user interactions.

Index GrowingIO analytics data directly into LlamaIndex vector stores for hallucination-free product analysis.

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Connect GrowingIO MCP to LlamaIndex

Create your Vinkius account to connect GrowingIO 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.

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Setup GrowingIO with LlamaIndex

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Semantic Search Over GrowingIO Events

Stop guessing why your GrowingIO numbers changed inside your LlamaIndex application. This MCP Server integration pulls raw data from `list_events` and `list_variables` and indexes them into your local LlamaIndex vector store. Your LlamaIndex agent queries this knowledge base to find GrowingIO correlations that standard dashboards miss. Instead of raw SQL, you ask LlamaIndex natural questions about your tracking setup. The index stores the outputs of `get_project_info` so your LlamaIndex agent always works with accurate, grounded GrowingIO metadata.

Knowledge-Augmented Funnel Analysis in LlamaIndex

Combine live GrowingIO conversion funnels with historical reports in LlamaIndex. By calling `get_funnel`, your LlamaIndex agent pulls real-time conversion rates and indexes them alongside your quarterly marketing plans. This lets your LlamaIndex RAG pipeline write reports that compare current performance against past projections. The LlamaIndex agent pulls GrowingIO segment data using `list_segments` to explain exactly which cohorts are driving the metrics.

Grounded Campaign Performance Queries

Verify GrowingIO ad performance in LlamaIndex without relying on manual spreadsheets. The MCP Server tool `list_ads` pulls active campaign details directly into your LlamaIndex index. Your LlamaIndex agent matches these campaigns against actual user sign-ups to calculate true acquisition costs. By querying `get_metrics` alongside your campaign data, the LlamaIndex agent spots underperforming ads. It bases these decisions on live GrowingIO analytics, eliminating the risk of LLM hallucinations.

Setup guide

Set up GrowingIO 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 GrowingIO 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 GrowingIO tools.",
)
response = await agent.run("List recent GrowingIO data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GrowingIO. 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.

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Common questions about GrowingIO MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize the MCP client. Convert the tools to a list of executable specifications and pass them to your LlamaIndex agent to start indexing your metrics.

Yes, your LlamaIndex agent can call `list_segments` to retrieve active groups. It then indexes these definitions so you can run semantic searches over your user cohorts.

Yes, the LlamaIndex agent can call `get_event` on demand to fetch live event metadata. This ensures your knowledge base stays updated with the latest user interactions.

Yes, you can use the allowed tools filter during initialization. This lets you restrict the LlamaIndex agent to specific endpoints like `get_project_info` while blocking access to user-level data.

The MCP Server runs in a secure, ephemeral sandbox that processes your funnel steps and event logs in memory. No data is cached on our servers, and your API credentials are encrypted end-to-end.

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