Invoiced MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Check Invoiced Status, Create Customer, Create Invoice, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Invoiced as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Invoiced app connector for LlamaIndex is a standout in the Erp Operations category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Invoiced. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Invoiced?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Invoiced MCP Server
Connect your Invoiced account to any AI agent and take full control of your accounts receivable orchestration and automated billing workflows through natural conversation.
LlamaIndex agents combine Invoiced 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
- Invoice Portfolio Orchestration — List and manage all issued invoices programmatically, retrieving detailed payment metadata and aging statuses
- Customer & Payment Intelligence — Programmatically retrieve directories of customers and access complete credit profiles and payment history in real-time
- A/R Workflow Architecture — Access your complete directory of payment plans and auto-pay settings to coordinate your organizational revenue
- Operational Monitoring — Access real-time status updates for paid invoices and track collection metrics directly through your agent for instant reporting
- Infrastructure Verification — Verify account-level API connectivity and monitor transaction volume directly through your agent for perfectly coordinated service scaling
The Invoiced 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.
All 10 Invoiced tools available for LlamaIndex
When LlamaIndex connects to Invoiced through Vinkius, your AI agent gets direct access to every tool listed below — spanning accounts-receivable, automated-billing, payment-reminders, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify Invoiced API connectivity
Create a customer
Pass line items as JSON array with name, quantity, and unit_cost. Create an invoice
Get customer details
Get invoice details
List all credit notes
List all customers
List all estimates
List all invoices
List all payments
Connect Invoiced to LlamaIndex via MCP
Follow these steps to wire Invoiced into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Invoiced MCP Server
LlamaIndex provides unique advantages when paired with Invoiced through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Invoiced tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Invoiced tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Invoiced, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Invoiced tools were called, what data was returned, and how it influenced the final answer
Invoiced + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Invoiced MCP Server delivers measurable value.
Hybrid search: combine Invoiced real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Invoiced 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 Invoiced for fresh data
Analytical workflows: chain Invoiced queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Invoiced in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Invoiced immediately.
"Show all unpaid invoices in my Invoiced account."
"Create an invoice for customer 5001 with 2 items."
"List all estimates waiting for approval."
Troubleshooting Invoiced MCP Server with LlamaIndex
Common issues when connecting Invoiced to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpInvoiced + LlamaIndex FAQ
Common questions about integrating Invoiced MCP Server with LlamaIndex.