How to Use the ChargeOver MCP in LlamaIndex

Q: How do I use the ChargeOver MCP Server with LlamaIndex?

Install llama-index-tools-mcp via pip. Initialize a BasicMCPClient with your Vinkius URL, wrap it in an McpToolSpec, and pass the async tool list to your agent.

Q: How do I limit which ChargeOver tools LlamaIndex can access?

Use the allowedtools filter when configuring the tool spec. You can restrict the agent to only reading invoices while blocking access to broader subscription lists.

Index your ChargeOver billing data into LlamaIndex to build searchable, hallucination-free finance assistants.

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Connect ChargeOver MCP to LlamaIndex

Create your Vinkius account to connect ChargeOver 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 ChargeOver with LlamaIndex

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Index invoices into vector stores

Your LlamaIndex application turns raw billing data into a semantic knowledge base. By calling `list_chargeover_invoices`, the framework pulls historical billing records and embeds them directly into your queryable index. Users ask questions about revenue trends and get answers grounded in actual database entries. The system reads the embedded text instead of guessing at past payment amounts.

Search ChargeOver MCP Server records

Give your RAG pipeline direct access to live subscription states. The agent executes `get_customer_details` and injects the current package tier into the prompt context before generating a response. Support teams get immediate answers about account limits. Instead of opening a dashboard, they query the index, which fetches the live data via the MCP integration and synthesizes a readable summary.

Ground answers in transaction logs

Financial queries require exact numbers, not approximations. When a user asks about a specific payment, the `FunctionAgent` triggers `list_billing_transactions` to retrieve the exact ledger entries. The retrieved data merges with your existing indexed documents. You can cross-reference a declined payment from the billing system with an indexed support ticket from your helpdesk.

Setup guide

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

Install `llama-index-tools-mcp` via pip. Initialize a `BasicMCPClient` with your Vinkius URL, wrap it in an `McpToolSpec`, and pass the async tool list to your agent.

Yes. The agent pulls the active sales proposals using the built-in tools and adds them to the context window. Your queries return exact pricing numbers pulled straight from the API.

Use the `allowed_tools` filter when configuring the tool spec. You can restrict the agent to only reading invoices while blocking access to broader subscription lists.

No. The MCP server fetches live data exactly when the user asks a question. The framework handles the API request and formats the response for the LLM automatically.

We process all requests through ephemeral zero-trust environments. When your agent queries customer billing tiers or payment histories, the sandbox executes the request and terminates. No persistent storage exists on the Vinkius side.

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