Guestmeter MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Guestmeter 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 Guestmeter. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Guestmeter?"
)
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 Guestmeter MCP Server
Connect your Guestmeter hospitality feedback platform to any AI agent and take full control of your reputation management workflows through natural conversation.
LlamaIndex agents combine Guestmeter tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Automated Surveys — Trigger satisfaction surveys via Email or SMS for guests immediately after checkout.
- Feedback Monitoring — List and inspect all guest ratings, comments, and NPS types (Promoters, Passives, Detractors).
- Reputation Insights — Retrieve detailed reports on specific guest experiences to identify areas for improvement.
- Real-time Alerts — Stay updated on the most recent feedback entries to respond quickly to guest concerns.
- Segmented Analysis — Filter feedback to focus on your happiest guests (Promoters) or those needing attention (Detractors).
The Guestmeter MCP Server exposes 6 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 Guestmeter to LlamaIndex via MCP
Follow these steps to integrate the Guestmeter 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 6 tools from Guestmeter
Why Use LlamaIndex with the Guestmeter MCP Server
LlamaIndex provides unique advantages when paired with Guestmeter through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Guestmeter tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Guestmeter tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Guestmeter, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Guestmeter tools were called, what data was returned, and how it influenced the final answer
Guestmeter + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Guestmeter MCP Server delivers measurable value.
Hybrid search: combine Guestmeter real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Guestmeter 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 Guestmeter for fresh data
Analytical workflows: chain Guestmeter queries with LlamaIndex's data connectors to build multi-source analytical reports
Guestmeter MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect Guestmeter to LlamaIndex via MCP:
get_guest_details
Retrieve detailed information for a specific guest ID
list_detractors
List all guests who are detractors (ratings 1-6)
list_guest_feedback
List all guests and their feedback status/results
list_promoters
List all guests who are promoters (ratings 9-10)
list_recent_feedback
List the 50 most recent feedback entries
send_survey
Requires either an email or phone number. Trigger a new guest satisfaction survey via Email or SMS
Example Prompts for Guestmeter in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Guestmeter immediately.
"List the most recent guest feedback entries."
"Send a survey to John Doe at john.doe@example.com for room 302."
"Show me all our detractors from the last batch."
Troubleshooting Guestmeter MCP Server with LlamaIndex
Common issues when connecting Guestmeter to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGuestmeter + LlamaIndex FAQ
Common questions about integrating Guestmeter 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 Guestmeter 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 Guestmeter to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.