ChargeOver MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ChargeOver 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 ChargeOver. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in ChargeOver?"
)
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 ChargeOver MCP Server
Connect your ChargeOver account to any AI agent and take full control of your recurring billing and invoicing operations through natural conversation. Streamline how you manage subscriptions and customer payments.
LlamaIndex agents combine ChargeOver tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Customer Oversight — List and retrieve details for all customer profiles and their contact information natively
- Invoice Management — Monitor generated invoices and their current payment status flawlessly
- Subscription Tracking — List and retrieve details for active and inactive customer packages securely
- Transaction Auditing — Access and monitor all billing transactions and payment history flawlessly
- Quote Control — List and review sales quotes to manage your revenue pipeline securely
- Account Visibility — Retrieve core account and user information directly within your workspace
The ChargeOver MCP Server exposes 8 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 ChargeOver to LlamaIndex via MCP
Follow these steps to integrate the ChargeOver 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 8 tools from ChargeOver
Why Use LlamaIndex with the ChargeOver MCP Server
LlamaIndex provides unique advantages when paired with ChargeOver through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ChargeOver tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ChargeOver tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ChargeOver, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ChargeOver tools were called, what data was returned, and how it influenced the final answer
ChargeOver + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ChargeOver MCP Server delivers measurable value.
Hybrid search: combine ChargeOver real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ChargeOver 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 ChargeOver for fresh data
Analytical workflows: chain ChargeOver queries with LlamaIndex's data connectors to build multi-source analytical reports
ChargeOver MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect ChargeOver to LlamaIndex via MCP:
get_chargeover_account
Retrieve core account and user information
get_customer_details
Get detailed information for a specific customer
get_invoice_details
Get detailed information for a specific invoice
list_billing_quotes
List all sales quotes
list_billing_subscriptions
List all customer subscriptions (packages)
list_billing_transactions
List all billing transactions
list_chargeover_customers
List all customers
list_chargeover_invoices
List all invoices
Example Prompts for ChargeOver in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with ChargeOver immediately.
"Show me the last 5 invoices in ChargeOver."
"List all customers with active subscriptions."
"What was my total transaction volume today?"
Troubleshooting ChargeOver MCP Server with LlamaIndex
Common issues when connecting ChargeOver to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpChargeOver + LlamaIndex FAQ
Common questions about integrating ChargeOver MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect ChargeOver with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ChargeOver to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.