Rappi API MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Rappi API as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Rappi API. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Rappi API?"
)
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 Rappi API MCP Server
Empower your intelligent agents directly with Rappi API, the dominant delivery and logistics super-app bridging Latin America. Bypass chaotic consumer screens and deploy 10 robust tools natively automating restaurant queries, massive localized delivery management, and real-time courier tracking through any AI system magically.
LlamaIndex agents combine Rappi API tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Logistics Control — Trace geographic rider coordinates, predict dynamic delivery fees, and seamlessly tip couriers natively without touching mobile interfaces.
- Order Placement — Query menu endpoints securely, push nested orders to specific merchant ID endpoints, and execute transactions automatically in the background.
- Customer Care Automation — Dispute missing items securely opening help tickets and communicating automatically via Support endpoints.
- Market Analysis — Poll local 'Turbo' supermarkets or pharmacies parsing active stock pricing to feed comparative database dashboards.
The Rappi API MCP Server exposes 10 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 Rappi API to LlamaIndex via MCP
Follow these steps to integrate the Rappi API 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 10 tools from Rappi API
Why Use LlamaIndex with the Rappi API MCP Server
LlamaIndex provides unique advantages when paired with Rappi API through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Rappi API tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Rappi API tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Rappi API, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Rappi API tools were called, what data was returned, and how it influenced the final answer
Rappi API + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Rappi API MCP Server delivers measurable value.
Hybrid search: combine Rappi API real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Rappi API 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 Rappi API for fresh data
Analytical workflows: chain Rappi API queries with LlamaIndex's data connectors to build multi-source analytical reports
Rappi API MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Rappi API to LlamaIndex via MCP:
get_order_detail
Get full details for a specific order
get_order_handoff
Get handoff confirmation codes for an order
get_store_availability
Check availability status of a store
get_store_menu
Retrieve the full menu of a store
list_new_orders
List new incoming orders awaiting acceptance
list_stores
List all registered stores under your account
mark_ready_for_pickup
Signal that an order is ready for courier pickup
reject_order
Reject an incoming order with a reason
take_order
Accept and start preparing an incoming order
update_store_status
Open or close a store for receiving orders
Example Prompts for Rappi API in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Rappi API immediately.
"List nearby stores in the 'pharmacy' category around coordinates 4.6097, -74.0817."
"Check the delivery state and ETA for my active order number 8812920."
"Cancel the active order 88910 immediately citing missing items from the receipt."
Troubleshooting Rappi API MCP Server with LlamaIndex
Common issues when connecting Rappi API to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRappi API + LlamaIndex FAQ
Common questions about integrating Rappi API 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 Rappi API 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 Rappi API to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.