Guestmeter MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Guestmeter through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"guestmeter": {
"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 Guestmeter, 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 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.
LangChain's ecosystem of 500+ components combines seamlessly with Guestmeter through native MCP adapters. Connect 6 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
- 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 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 Guestmeter to LangChain via MCP
Follow these steps to integrate the Guestmeter 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 6 tools from Guestmeter via MCP
Why Use LangChain with the Guestmeter MCP Server
LangChain provides unique advantages when paired with Guestmeter through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Guestmeter 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 Guestmeter queries for multi-turn workflows
Guestmeter + LangChain Use Cases
Practical scenarios where LangChain combined with the Guestmeter MCP Server delivers measurable value.
RAG with live data: combine Guestmeter tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Guestmeter, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Guestmeter tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Guestmeter tool call, measure latency, and optimize your agent's performance
Guestmeter MCP Tools for LangChain (6)
These 6 tools become available when you connect Guestmeter to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Guestmeter to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGuestmeter + LangChain FAQ
Common questions about integrating Guestmeter 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 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 LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.