How to Use the Funil de Vendas MCP in LlamaIndex

Q: How does the Funil de Vendas MCP Server work with LlamaIndex?

You use the llama-index-tools-mcp package to create an McpToolSpec. This exposes all 12 Funil de Vendas tools, which you can then add to your agent or use to build a knowledge base from your CRM data.

Q: Can I use LlamaIndex to search my deals in Funil de Vendas?

Yes, that's the core idea. You run tools like listcrmopportunities and feed the results into a LlamaIndex vector store. Then you can perform semantic searches over your entire deal history.

Q: How do I get my list of custom fields from Funil de Vendas with LlamaIndex?

Your agent can call the listcrmcustomfields tool. This is useful for ensuring new leads created via createnewdeallead have all the required custom data filled in.

Q: Can I add new leads to Funil de Vendas through LlamaIndex?

Absolutely. Your agent can call the createnewdeallead tool directly. This is useful for RAG applications that parse unstructured text, like an email, and decide to create a new lead from it.

Use LlamaIndex to index your Funil de Vendas data. Build RAG apps that answer questions with live, accurate CRM info.

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Connect Funil de Vendas MCP to LlamaIndex

Create your Vinkius account to connect Funil de Vendas 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 Funil de Vendas with LlamaIndex

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Perplexity

Turn your CRM into a knowledge base

Stop guessing. Use LlamaIndex to index the output of tools like `list_crm_opportunities` and `list_crm_products`. This creates a searchable vector index of your actual sales data. Now you can ask complex questions in natural language. 'Show me all deals we lost last quarter and why' becomes a query that pulls from indexed `list_loss_motives` data, giving you an answer grounded in facts, not a guess.

Query your sales process

Your agent can do more than just fetch data; it can understand it. By indexing the results of `list_sales_funnels` and `list_lead_origins`, your RAG application can answer questions about your sales process itself. Ask 'What are our top lead sources for the 'Enterprise' funnel?' Your agent can cross-reference the indexed data to give you a precise answer. It's about combining live data with a persistent, searchable memory of your CRM's state.

Ground your LlamaIndex agent with live data

The `McpToolSpec` makes every Funil de Vendas tool available to your LlamaIndex agent. It can query the knowledge you've indexed, but it can also fetch live data with `list_crm_activities` to get the absolute latest status. This MCP Server provides the live connection. Your agent gets the best of both worlds: the deep context of your indexed CRM history and the real-time accuracy of a direct API call. This prevents stale data and ensures your agent's responses are current.

Setup guide

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

You use the `llama-index-tools-mcp` package to create an `McpToolSpec`. This exposes all 12 Funil de Vendas tools, which you can then add to your agent or use to build a knowledge base from your CRM data.

Yes, that's the core idea. You run tools like `list_crm_opportunities` and feed the results into a LlamaIndex vector store. Then you can perform semantic searches over your entire deal history.

Your agent can call the `list_crm_custom_fields` tool. This is useful for ensuring new leads created via `create_new_deal_lead` have all the required custom data filled in.

Absolutely. Your agent can call the `create_new_deal_lead` tool directly. This is useful for RAG applications that parse unstructured text, like an email, and decide to create a new lead from it.

Yes. Your CRM opportunity and product data is fetched through the Vinkius MCP Server using a single auth token. How and where you store the index is up to you, but the connection itself is isolated and secured.

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