Can I check the payment status of an invoice using the agent?

Yes! Use the `get_invoice` tool with the Invoice ID. Your agent will fetch the latest status, showing if it is draft, issued, or paid.

How do I list all my customers in Bexio?

Simply ask the agent to `list_contacts`. It will retrieve the directory of all companies and persons registered in your Bexio account.

Does the integration allow me to create a new invoice?

Currently, the toolset is focused on querying and management (listing contacts, checking projects, auditing invoices). For creating complex financial documents like invoices with multiple line items, we recommend using the Bexio platform directly.

Bexio MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Bexio
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bexio as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Bexio. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Bexio?"
    )
    print(response)

asyncio.run(main())

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About Bexio MCP Server

Connect your Bexio account to any AI agent and orchestrate your business workflows, including CRM, accounting, and project management, through natural conversation.

LlamaIndex agents combine Bexio tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Contact Management — List, create, and retrieve detailed information for customers, suppliers, and partners.
Invoicing & Sales — Query invoices, offers, and orders to stay on top of your sales pipeline and receivables.
Project Oversight — List all business projects and monitor their status and progress.
Inventory & Items — Access your product catalog and list items with pricing and stock metadata.
Team Collaboration — Retrieve lists of users within your Bexio organization for better task coordination.

The Bexio MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Bexio to LlamaIndex via MCP

Follow these steps to integrate the Bexio MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Bexio

Why Use LlamaIndex with the Bexio MCP Server

LlamaIndex provides unique advantages when paired with Bexio through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Bexio tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Bexio tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Bexio, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Bexio tools were called, what data was returned, and how it influenced the final answer

Bexio + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Bexio MCP Server delivers measurable value.

Hybrid search: combine Bexio real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Bexio to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Bexio for fresh data

Analytical workflows: chain Bexio queries with LlamaIndex's data connectors to build multi-source analytical reports

Bexio MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Bexio to LlamaIndex via MCP:

create_contact

Create a new contact

get_contact

Get specific contact details

get_invoice

Get specific invoice details

list_contacts

List all contacts

list_invoices

List all invoices

list_items

List all products/items

list_offers

List all offers

list_orders

List all orders

list_projects

List all projects

list_users

List all Bexio users

Example Prompts for Bexio in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Bexio immediately.

"List all active projects in Bexio."

"Find the contact details for 'Acme Corp'."

"Show my last 5 invoices."

Troubleshooting Bexio MCP Server with LlamaIndex

Common issues when connecting Bexio to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Bexio + LlamaIndex FAQ

Common questions about integrating Bexio MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.