kvCORE MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect kvCORE through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
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({
"kvcore": {
"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 kvCORE, 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 kvCORE MCP Server
Connect your AI agent to kvCORE, the primary platform for real estate professionals to manage their entire business.
LangChain's ecosystem of 500+ components combines seamlessly with kvCORE through native MCP adapters. Connect 10 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.
Key Features
- Lead Management — Search and audit lead profiles, update statuses, and add manual notes through natural language
- Listing Intelligence — Access active property listings and detailed metadata including features and pricing
- Marketing Visibility — List and monitor smart campaigns and automated marketing sequences
- Agent Workflow — Audit pending tasks, reminders, and recent lead activities to stay on top of follow-ups
- Profile Insights — Fetch agent profile data and high-level account configuration
Simple Setup
1. Subscribe to this server
2. Log in to kvCORE, go to Settings > API, and generate an API Key
3. Enter your key in the configuration panel
4. Start managing your real estate business via chat
The kvCORE MCP Server exposes 10 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 kvCORE to LangChain via MCP
Follow these steps to integrate the kvCORE 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 10 tools from kvCORE via MCP
Why Use LangChain with the kvCORE MCP Server
LangChain provides unique advantages when paired with kvCORE through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine kvCORE 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 kvCORE queries for multi-turn workflows
kvCORE + LangChain Use Cases
Practical scenarios where LangChain combined with the kvCORE MCP Server delivers measurable value.
RAG with live data: combine kvCORE tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query kvCORE, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain kvCORE tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every kvCORE tool call, measure latency, and optimize your agent's performance
kvCORE MCP Tools for LangChain (10)
These 10 tools become available when you connect kvCORE to LangChain via MCP:
create_lead_note
Add a note to a lead profile
get_agent_profile
Get current agent information
get_lead_details
Get details for a specific lead
get_listing_details
Get metadata for a specific listing
list_agent_tasks
List pending tasks for the agent
list_lead_activity
List recent activity for a lead
list_marketing_campaigns
List all marketing campaigns
list_property_listings
List active property listings
search_kvcore_leads
Returns lead IDs and basic contact info. Search for leads in kvCORE
update_lead_info
g., status, phone). Provide data as a JSON string. Update an existing lead
Example Prompts for kvCORE in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with kvCORE immediately.
"Search for a lead named 'Alice' in my kvCORE"
"Show me details for the property at '123 Maple St'"
"List my tasks for today"
Troubleshooting kvCORE MCP Server with LangChain
Common issues when connecting kvCORE to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adapterskvCORE + LangChain FAQ
Common questions about integrating kvCORE 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 kvCORE 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 kvCORE to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.