How to Use the FunnelCockpit MCP in LlamaIndex

Q: Can I use LlamaIndex to ask questions about my FunnelCockpit campaigns?

Yes, that's the core idea. You index the output of listcampaigns, and then you can ask LlamaIndex "what was our best performing campaign last quarter?" and get an answer based on real data.

Build a RAG system on your live FunnelCockpit marketing data with LlamaIndex. Index funnels, campaigns, and contacts for semantic search.

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Connect FunnelCockpit MCP to LlamaIndex

Create your Vinkius account to connect FunnelCockpit 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 FunnelCockpit with LlamaIndex

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Index Your Marketing Funnels

Connect LlamaIndex to FunnelCockpit and turn your marketing assets into a queryable knowledge base. The system can call `list_funnels` and `list_pages` to automatically index the structure and content of your entire sales setup. Now you can ask questions in natural language, like "Which funnels are targeting our European market?" LlamaIndex will find the answer by searching the indexed data from those tool calls, not by guessing.

Query Contacts with Semantic Search

This goes way beyond simple database lookups. By indexing the output of `list_contacts`, you create a semantic index of your customer base. You're not just filtering by tags; you're searching by intent. Ask "Show me contacts who recently engaged with our launch campaign but didn't buy." LlamaIndex can interpret the query, use the indexed data from `get_contact` and `list_campaigns`, and give you a precise list.

Ground Answers in Live MCP Server Data

Stop getting hallucinated answers about your marketing performance. LlamaIndex agents can be configured to call FunnelCockpit tools like `get_funnel` in real-time to answer a query. When you ask for the conversion rate of a specific funnel, the agent doesn't use stale, month-old data. It calls `get_funnel` right then and there, pulls the latest stats, and gives you an answer grounded in live information from the MCP server.

Setup guide

Set up FunnelCockpit 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 FunnelCockpit 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 FunnelCockpit tools.",
)
response = await agent.run("List recent FunnelCockpit 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 FunnelCockpit. 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 FunnelCockpit MCP in LlamaIndex

Yes, that's the core idea. You index the output of `list_campaigns`, and then you can ask LlamaIndex "what was our best performing campaign last quarter?" and get an answer based on real data.

You can set up your LlamaIndex application to periodically re-index the data. It will call `list_contacts` again, find the new entries, and add them to its knowledge base so your queries are always up-to-date.

A great starting point is to build a "Funnel-Finder" bot. Have LlamaIndex index all your funnels using `list_funnels`, then build a simple chat interface that lets your marketing team ask questions to find the right funnel for their next campaign.

It can. While LlamaIndex is primarily for querying, you can build an agent that uses tools. So after finding information, you could have it execute `create_contact` to add a new lead based on a conversation.

You control where the index is stored. This MCP server simply provides the raw contact data from `list_contacts` through a secure, isolated connection. It's up to you to manage the resulting vector index according to your own security policies.

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