ChargeOver MCP Server for LangChain 8 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect ChargeOver through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"chargeover": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using ChargeOver, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with ChargeOver through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the ChargeOver MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 8 tools from ChargeOver via MCP
Why Use LangChain with the ChargeOver MCP Server
LangChain provides unique advantages when paired with ChargeOver through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine ChargeOver MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across ChargeOver queries for multi-turn workflows
ChargeOver + LangChain Use Cases
Practical scenarios where LangChain combined with the ChargeOver MCP Server delivers measurable value.
RAG with live data: combine ChargeOver tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query ChargeOver, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain ChargeOver tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every ChargeOver tool call, measure latency, and optimize your agent's performance
ChargeOver MCP Tools for LangChain (8)
These 8 tools become available when you connect ChargeOver to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting ChargeOver to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersChargeOver + LangChain FAQ
Common questions about integrating ChargeOver MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.