How to Use the Invoiced MCP in LangChain

Q: How do I connect the Invoiced MCP Server to my LangChain agent?

Install langchain-mcp-adapters and langgraph via pip to bootstrap the Invoiced connection. You then initialize MultiServerMCPClient with your Vinkius endpoint and pass the Invoiced tools directly to your LangChain agent constructor.

Q: Can LangChain track the latency of Invoiced tool calls?

Yes, every LangChain call to listinvoices or getcustomer is fully visible inside LangSmith tracing. You can monitor execution speed, token counts, and the exact payloads returned from the Invoiced billing API.

Q: How does LangChain handle multi-server setups with Invoiced?

The MultiServerMCPClient aggregates tools from your Invoiced server alongside other connected services. This lets your LangChain agent pull a customer profile from one tool and immediately check their billing history with getinvoice in a single execution loop.

Q: Can I use LangChain to check tax rates via Invoiced?

Yes, your LangChain agent can call listtaxrates to retrieve active Invoiced tax percentages during a multi-step billing calculation. This keeps your LangChain tax calculations grounded in live Invoiced data without manual lookups.

Run multi-step billing audits and payment reconciliations by feeding live Invoiced accounts receivable data into your LangChain chains.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Invoiced MCP to LangChain

Create your Vinkius account to connect Invoiced to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Invoiced with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build LangChain ReAct chains for instant billing audits

The `list_invoices` tool gives your LangChain agent immediate access to outstanding Invoiced customer balances and billing records. This tool serves as the starting point for LangChain chains that need to flag overdue accounts before triggering collection sequences. Instead of hardcoding rules, you let your LangChain agent check payment histories with `list_payments` to decide if an Invoiced account needs manual intervention. LangSmith tracks every tool call in the sequence, showing you exactly how the LangChain agent navigated from the initial Invoiced list to the final settlement status.

Route discount questions through dynamic chains

This MCP tool lets your LangChain agent inspect active promotional codes from Invoiced directly within a routing chain. Your LangChain agent uses `list_coupons` to verify whether a customer's requested discount matches your active Invoiced marketing promotions. By linking this step to `get_customer`, the LangChain agent can evaluate if a specific Invoiced account is eligible for a rate adjustment. The entire decision flow runs inside your LangGraph state, passing the validated Invoiced coupon data directly to your customer support team.

Automate subscription drift detection

The `list_subscriptions` tool pulls active customer plans from Invoiced so your LangChain agent can compare current billing states against your internal database records. It exposes Invoiced MRR details and active plans to help your LangChain agent identify discrepancies in recurring revenue. You can feed this Invoiced subscription data straight into a LangChain vector store or compare it with `list_plans` to spot accounts on retired pricing tiers. This setup turns raw Invoiced billing data into structured inputs for your downstream LangChain automated reporting pipelines.

Setup guide

Set up Invoiced MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Invoiced tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "invoiced-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Invoiced transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Invoiced. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Invoiced now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Invoiced MCP in LangChain

Install `langchain-mcp-adapters` and `langgraph` via pip to bootstrap the Invoiced connection. You then initialize `MultiServerMCPClient` with your Vinkius endpoint and pass the Invoiced tools directly to your LangChain agent constructor.

Yes, every LangChain call to `list_invoices` or `get_customer` is fully visible inside LangSmith tracing. You can monitor execution speed, token counts, and the exact payloads returned from the Invoiced billing API.

The `MultiServerMCPClient` aggregates tools from your Invoiced server alongside other connected services. This lets your LangChain agent pull a customer profile from one tool and immediately check their billing history with `get_invoice` in a single execution loop.

Yes, your LangChain agent can call `list_tax_rates` to retrieve active Invoiced tax percentages during a multi-step billing calculation. This keeps your LangChain tax calculations grounded in live Invoiced data without manual lookups.

Vinkius runs this server inside an isolated V8 sandbox, ensuring your Invoiced customer balances and API keys are never exposed. Your LangChain agent only receives the specific JSON payloads returned by tools like `get_customer` over an encrypted, ephemeral connection.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript