How to Use the Hostfully MCP in LangChain
LangChain agents now run your Hostfully vacation rentals by chaining property, lead, and guest data directly into multi-step runs.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Hostfully MCP to LangChain
Create your Vinkius account to connect Hostfully to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Chain property lookups directly to guest communication
LangChain chains together your Hostfully listings and guest queries without manual scripting. When a guest asks about a specific house, your agent uses `list_properties` to pull current listings, feeds the output to the next step, and runs `get_property` to grab the exact check-in details. You do not write glue code to pass variables between these steps. The output of the property lookup feeds the prompt template for the next chain link automatically, letting your agent draft personalized replies based on real-time rental data.
Trace reservation lead pipelines in LangSmith
Stop guessing why your booking agent failed to close a lead. By exposing `list_leads` and `get_lead` as tools to your LangChain agent, every decision, tool call, and token count gets logged in LangSmith so you can debug latency issues instantly. If an agent fails to match a lead with an owner using `list_owners`, you will see the exact JSON payload that broke the chain. This visibility keeps your vacation rental pipeline running without silent failures or dropped bookings.
Run multi-step property operations
Run complex workflows that span multiple Hostfully endpoints in a single execution. Your agent uses `list_webhooks` to monitor incoming booking events, then immediately triggers `list_service_providers` to assign cleaners to the newly booked property. This MCP setup allows your LangChain run to dynamically decide which service provider to contact based on the agency details retrieved via `get_agency`. You get a self-correcting operations flow that adapts as your reservation data changes.
Set up Hostfully MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"transport": "http"pointing to your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Create a ReAct agent
Pass the discovered tools to
create_react_agent()from LangGraph. The agent automatically routes Hostfully tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"hostfully-mcp": {
"transport": "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,
)
result = await agent.ainvoke({
"messages": "List recent Hostfully transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hostfully. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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place for every integration
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Common questions about Hostfully MCP in LangChain
Use it with your favorite AI tools
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