PedidosYa MCP Server for LangChain 14 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect PedidosYa 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({
"pedidosya": {
"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 PedidosYa, 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 PedidosYa MCP Server
Connect your PedidosYa partner account to any AI agent and manage the full delivery lifecycle across Latin America's leading food delivery platform.
LangChain's ecosystem of 500+ components combines seamlessly with PedidosYa through native MCP adapters. Connect 14 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
- Order Management — Receive, accept, reject, and mark orders as ready for pickup, all through natural conversation without touching the partner tablet
- Menu Control — Toggle products on/off (sold out) and update prices in real-time on your live PedidosYa listing
- Courier Logistics — Request on-demand PedidosYa couriers for B2B deliveries and track their GPS position in real-time
- Venue Management — Query all your registered restaurants, their operating hours, preparation times, and marketplace performance
- Webhook Automation — Configure event-driven webhooks for new orders, cancellations, and courier assignments
The PedidosYa MCP Server exposes 14 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 PedidosYa to LangChain via MCP
Follow these steps to integrate the PedidosYa 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 14 tools from PedidosYa via MCP
Why Use LangChain with the PedidosYa MCP Server
LangChain provides unique advantages when paired with PedidosYa through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine PedidosYa 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 PedidosYa queries for multi-turn workflows
PedidosYa + LangChain Use Cases
Practical scenarios where LangChain combined with the PedidosYa MCP Server delivers measurable value.
RAG with live data: combine PedidosYa tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query PedidosYa, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain PedidosYa tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every PedidosYa tool call, measure latency, and optimize your agent's performance
PedidosYa MCP Tools for LangChain (14)
These 14 tools become available when you connect PedidosYa to LangChain via MCP:
accept_order
Once accepted, the restaurant commits to preparing the items within the estimated preparation time. The PedidosYa system will begin assigning a delivery courier. Accept a pending order
create_webhook
g., new_order, order_cancelled, courier_assigned, order_delivered). Create a new webhook subscription
get_order
Get full details of a specific order
get_restaurant
Get details of a specific restaurant
list_menu_sections
g., Entradas, Platos Principales, Bebidas, Postres). Each section contains its products with prices, descriptions, and availability status. List menu sections and products for a restaurant
list_orders
Filter by status to find pending orders requiring acceptance, orders being prepared, orders ready for pickup, or completed deliveries. List incoming orders
list_restaurants
Each venue includes its operating status, delivery radius, and current open/closed state. List your partner restaurants
list_webhooks
). List configured webhooks
mark_order_ready
This triggers the courier dispatch if one hasn't already arrived. Mark an order as ready for courier pickup
reject_order
Valid rejection reasons include: out_of_stock, closing_soon, too_busy, item_unavailable. Frequent rejections may affect your venue's ranking on the platform. Reject a pending order
request_courier
Used for scheduling on-demand courier pickups, ideal for B2B deliveries outside the regular order flow. Specify the pickup and dropoff addresses and package details. Request a PedidosYa courier for a delivery
track_shipment
Track a courier shipment in real-time
update_product_price
Price changes take effect immediately on the marketplace listing. The price should be in the local currency of the venue's country. Update the price of a menu product
update_product_status
Use this to mark items as temporarily unavailable (sold out) or to bring them back online without editing the full menu. Toggle a menu product on or off
Example Prompts for PedidosYa in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with PedidosYa immediately.
"Show me all pending orders for my restaurant."
"Mark the Chocotorta as sold out on restaurant ID R-4421."
"Request a courier to pick up a package from Av. 18 de Julio 1234, Montevideo and deliver to Rambla Wilson 500."
Troubleshooting PedidosYa MCP Server with LangChain
Common issues when connecting PedidosYa to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersPedidosYa + LangChain FAQ
Common questions about integrating PedidosYa 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 PedidosYa 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 PedidosYa to LangChain
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.