How to Use the WhoisXML MCP in LangChain
Build complex domain intelligence workflows with LangChain's ReAct agents.
Works with every AI agent you already use
…and any MCP-compatible client
Connect WhoisXML MCP to LangChain
Create your Vinkius account to connect WhoisXML 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.
Chaining Domain Checks with MCP Server
The `check_domain_availability` tool immediately tells you if a domain is open for registration. You can chain this output: check availability, then pass the result to `get_whois_record` to see who previously owned it. This multi-step process lets your agent build an entire intelligence pipeline based on real data flows.
IP Location and Email Validation
You can start by getting location data for any IP address using `get_ip_geolocation`. Next, pass the associated domain name into `verify_email` to confirm if a specific contact point is active. It's perfect for agents that need to vet both network infrastructure and human contacts in sequence.
Advanced Data Retrieval Pipelines
The core of the MCP Server lets you pull deep data using `get_whois_record`. This raw WHOIS output can then feed directly into a custom prompt that summarizes ownership history. This guarantees your agent performs complex, sequential reasoning, making every tool call a measurable link in the chain.
Set up WhoisXML 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 WhoisXML 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({
"whoisxml-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 WhoisXML 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 WhoisXML API. 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
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
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
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about WhoisXML MCP in LangChain
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the WhoisXML MCP today
We host it, we monitor it, we maintain it. You just paste one token.