How many restaurants use Toast?

Toast powers 112,000+ restaurants in the US — from food trucks and cafes to fine dining and multi-unit chains. It's the #1 restaurant POS platform.

Toast MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Toast
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Toast 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({
        "toast": {
            "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 Toast, 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 Toast MCP Server

Connect your Toast restaurant to any AI agent and transform how you run your business.

LangChain's ecosystem of 500+ components combines seamlessly with Toast through native MCP adapters. Connect 10 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

Orders — Browse today's sales, drill into check details, track voids and comps
Menus — Full menu engineering: items, prices, modifiers, and availability
Labor — Employee rosters, clock-in/out, overtime, and labor cost tracking
Tables — Floor plan, seating status, and section management
Payments — Cash, card, tips, and settlement tracking
Revenue Centers — Bar vs dining room vs patio sales segmentation

The Toast MCP Server exposes 10 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 Toast to LangChain via MCP

Follow these steps to integrate the Toast 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 10 tools from Toast via MCP

Why Use LangChain with the Toast MCP Server

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

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

Toast + LangChain Use Cases

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

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

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

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

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

Toast MCP Tools for LangChain (10)

These 10 tools become available when you connect Toast to LangChain via MCP:

get_order

Deep drill into a single check. Get order details

get_restaurant

Get restaurant info

list_dining_options

With behavior settings and online ordering config. List dining options

list_employees

For labor management. List employees

list_menu_items

"What is our most expensive dish?" List menu items

list_menus

With categories, availability windows, and ordering channels. List restaurant menus

list_orders

THE core tool — "What sold today?" List restaurant orders

list_revenue_centers

Used for sales segmentation and reporting. List revenue centers

list_tables

For floor plan and seating management. List restaurant tables

list_time_entries

For payroll and scheduling. List time entries

Example Prompts for Toast in LangChain

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

"What were our total sales yesterday and what was the most popular item?"

"Check today's gross sales across all our restaurant locations."

"Update the price of 'Avocado Toast' on the brunch menu to $12.50."

Troubleshooting Toast MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Toast + LangChain FAQ

Common questions about integrating Toast 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.