SevenRooms MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SevenRooms 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 SevenRooms. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in SevenRooms?"
)
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 SevenRooms MCP Server
Connect your SevenRooms restaurant to any AI agent — the premium hospitality CRM.
LlamaIndex agents combine SevenRooms tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Reservations — Tonight's covers, VIP arrivals, special occasions
- Guest CRM — Complete profiles: visit history, spend, preferences, allergies
- Waitlist — Real-time queue management with estimated wait times
- Availability — Open time slots for any party size and date
- Events — Wine dinners, chef tables, private dining
- Multi-venue — Cross-restaurant group analytics
The SevenRooms MCP Server exposes 8 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 SevenRooms to LlamaIndex via MCP
Follow these steps to integrate the SevenRooms 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 8 tools from SevenRooms
Why Use LlamaIndex with the SevenRooms MCP Server
LlamaIndex provides unique advantages when paired with SevenRooms through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SevenRooms tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SevenRooms tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SevenRooms, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SevenRooms tools were called, what data was returned, and how it influenced the final answer
SevenRooms + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SevenRooms MCP Server delivers measurable value.
Hybrid search: combine SevenRooms real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SevenRooms 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 SevenRooms for fresh data
Analytical workflows: chain SevenRooms queries with LlamaIndex's data connectors to build multi-source analytical reports
SevenRooms MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect SevenRooms to LlamaIndex via MCP:
check_availability
Shows open tables, wait times, and dining room options. Check table availability
get_guest
Get guest profile
get_reservation
Get reservation details
list_events
With date, capacity, pricing, and availability. List restaurant events
list_reservations
"Who is dining tonight?" List restaurant reservations
list_venues
For multi-location restaurant groups. List restaurant venues
list_waitlist
For real-time host management. List waitlist
search_guests
"Tell me about Mr. Silva." Search guest profiles
Example Prompts for SevenRooms in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SevenRooms immediately.
"Who are the VIP guests dining tonight and what are their preferences?"
"Check availability for a party of 4 this Friday at 8 PM."
"What events are scheduled for next month?"
Troubleshooting SevenRooms MCP Server with LlamaIndex
Common issues when connecting SevenRooms to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSevenRooms + LlamaIndex FAQ
Common questions about integrating SevenRooms 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 SevenRooms 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 SevenRooms to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.