Can I access data from multiple accounting platforms like QuickBooks and Xero simultaneously?

Yes! Railz normalizes data across all supported providers. Use the `list_businesses` and `list_connections` tools to identify the target entity, then query reports which will return in a consistent format regardless of the underlying source.

How do I retrieve a Balance Sheet for a specific company connection?

First, find the relevant `connection_id` for the business using `list_connections`. Then, use the `get_balance_sheet` tool with that ID to fetch the snapshot of assets and liabilities.

Does this integration allow creating new invoices or only reading them?

The current toolset focuses on read-only operations for auditing and analysis, such as `list_invoices`, `list_bills`, and `list_accounts`. This ensures safe exploration of financial data without accidental modifications.

Railz MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Railz
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Railz through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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({
        "railz": {
            "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 Railz, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Railz MCP Server

Empower your AI agent to access normalized financial data from various accounting, banking, and commerce platforms with Railz. By connecting Railz to your agent, you transform complex financial auditing into a natural conversation. Your agent can instantly list businesses, audit invoices, and retrieve deep financial reports like Balance Sheets and P&L statements without you ever touching a dashboard. Whether you are managing multiple client accounts or a single corporate entity, your agent acts as a real-time financial analyst, ensuring your data is always accessible and structured.

LangChain's ecosystem of 500+ components combines seamlessly with Railz through native MCP adapters. Connect 12 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

Business Directory — List all registered businesses in your Railz account and inspect their specific metadata.
Connection Auditing — Monitor active service provider connections (QuickBooks, Xero, Shopify, etc.) for any business entity.
Financial Reporting — Fetch real-time, normalized reports including Balance Sheets, Profit & Loss, and Cash Flow statements.
Invoice & Bill Management — Query and analyze accounts receivable (invoices) and accounts payable (bills) across multiple providers.
Commerce Insights — Access sales orders and transaction data from connected commerce platforms to track revenue trends.

The Railz MCP Server exposes 12 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 Railz to LangChain via MCP

Follow these steps to integrate the Railz 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 12 tools from Railz via MCP

Why Use LangChain with the Railz MCP Server

LangChain provides unique advantages when paired with Railz through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Railz 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 Railz queries for multi-turn workflows

Railz + LangChain Use Cases

Practical scenarios where LangChain combined with the Railz MCP Server delivers measurable value.

RAG with live data: combine Railz tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Railz, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Railz tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Railz tool call, measure latency, and optimize your agent's performance

Railz MCP Tools for LangChain (12)

These 12 tools become available when you connect Railz to LangChain via MCP:

get_balance_sheet

Get balance sheet report

get_business

Get details for a specific business

get_cash_flow

Get cash flow statement

get_profit_and_loss

Get profit and loss report

list_accounts

List chart of accounts

list_bank_transactions

List bank transactions

list_bills

List bills for a business

list_businesses

List all businesses in Railz

list_commerce_orders

g., Shopify, BigCommerce). List commerce orders

list_connections

g., QuickBooks, Xero) for a given business. List connections for a business

list_invoices

List invoices for a business

list_journal_entries

List journal entries

Example Prompts for Railz in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Railz immediately.

"List all businesses registered in my Railz account."

"Show active connections for business 'biz_123'."

"Get the Profit and Loss report for connection 'conn_456'."

Troubleshooting Railz MCP Server with LangChain

Common issues when connecting Railz to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Railz + LangChain FAQ

Common questions about integrating Railz MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.