PedidosYa MCP Server for LlamaIndex 14 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PedidosYa as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to PedidosYa. "
"You have 14 tools available."
),
)
response = await agent.run(
"What tools are available in PedidosYa?"
)
print(response)
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.
LlamaIndex agents combine PedidosYa tool responses with indexed documents for comprehensive, grounded answers. Connect 14 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the PedidosYa MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 14 tools from PedidosYa
Why Use LlamaIndex with the PedidosYa MCP Server
LlamaIndex provides unique advantages when paired with PedidosYa through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PedidosYa tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PedidosYa tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PedidosYa, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PedidosYa tools were called, what data was returned, and how it influenced the final answer
PedidosYa + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PedidosYa MCP Server delivers measurable value.
Hybrid search: combine PedidosYa real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PedidosYa to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying PedidosYa for fresh data
Analytical workflows: chain PedidosYa queries with LlamaIndex's data connectors to build multi-source analytical reports
PedidosYa MCP Tools for LlamaIndex (14)
These 14 tools become available when you connect PedidosYa to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting PedidosYa to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPedidosYa + LlamaIndex FAQ
Common questions about integrating PedidosYa MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect PedidosYa with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
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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.
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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 LlamaIndex
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.