How to Use the everbill MCP in LlamaIndex

Q: How can I use LlamaIndex to find an old everbill invoice?

First, you'd run a script to index your data using the listinvoices tool. After that, you can query your LlamaIndex application with the invoice number or customer name to find it instantly from your vector store.

Q: What's the difference between calling getinvoice directly and using a LlamaIndex query on everbill data?

Calling getinvoice gets you live data for one specific invoice. A LlamaIndex query searches across all the invoice data you've previously indexed, letting you find trends and ask broader questions.

Turn your everbill history into a searchable knowledge base with LlamaIndex and this MCP server to answer questions about your business.

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Connect everbill MCP to LlamaIndex

Create your Vinkius account to connect everbill 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 everbill with LlamaIndex

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Ask Questions, Get Answers

This isn't just about calling tools; it's about remembering what they returned. Use LlamaIndex to run `list_invoices` and `list_customers`, then index the results into a vector store. Now you have a memory for your business. Next time, instead of running another API call, you can just ask your RAG app, "What was the total for invoice #INV-003?" or "Show me all invoices for Client X". The answer comes from the indexed data, grounded in facts from your everbill account.

Build a Financial Chatbot

The everbill MCP Server gives LlamaIndex the raw data it needs. You can build a query engine that combines data from `get_invoice` and `get_customer` to answer complex questions about your freelance finances. It's like having a junior accountant on standby. Your agent can retrieve an invoice, see the customer ID, and then automatically pull the customer's details to provide a full picture. All of this happens in the background to answer one simple question from you.

Context from Your MCP Server

When you're creating an invoice, you need product info. Your LlamaIndex agent can use `list_products` to fetch your services and their prices. It can then index this information for faster lookups later on. This means your agent can help you build an invoice without you needing to remember every single product code or price. You just tell it what service you provided, and it finds the right data from its indexed knowledge of your everbill account.

Setup guide

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

First, you'd run a script to index your data using the `list_invoices` tool. After that, you can query your LlamaIndex application with the invoice number or customer name to find it instantly from your vector store.

LlamaIndex itself doesn't, but the vector store you connect it to will. You have full control over where the indexed results from tools like `list_customers` are stored, whether it's local or in the cloud.

Yes. You can build a RAG pipeline that indexes all data from `list_invoices`. Then, you can ask questions like "What was my total revenue last quarter?" and LlamaIndex will synthesize an answer from the indexed everbill data.

Calling `get_invoice` gets you live data for one specific invoice. A LlamaIndex query searches across all the invoice data you've previously indexed, letting you find trends and ask broader questions.

Yes. The MCP server sends customer profile data to your LlamaIndex agent over a secure connection. You are responsible for the security of the vector database where you choose to index that sensitive information.

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