4D MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect 4D 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({
"4d": {
"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 4D, 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 4D MCP Server
Bridge your 4D Server with the world of AI Agents through the power of ORDA (Object Relational Data Architecture). This integration transforms your 4D database into an intelligent, queryable knowledge base, allowing your AI agent to explore structures and manage records through natural conversation. No more manual REST calls; your agent can now audit catalogs, run complex entity queries, and perform high-speed CRUD operations, ensuring your 4D data is always accessible and actionable within your AI workflows.
LangChain's ecosystem of 500+ components combines seamlessly with 4D 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
- Database Exploration — Retrieve the full catalog of DataClasses (tables) and their attribute definitions (fields) to map your data structure.
- Advanced Querying — Perform complex data lookups using filters, ordering, and expansion of related entities with ORDA syntax.
- CRUD Operations — Create, read, update, and delete records across any exposed DataClass in your 4D environment.
- Metadata Insights — Check server information, version, and database structure on the fly to ensure system integrity.
- Structured Access — Interact with your data using the modern ORDA model, ensuring consistency, type safety, and security.
The 4D 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 4D to LangChain via MCP
Follow these steps to integrate the 4D 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 4D via MCP
Why Use LangChain with the 4D MCP Server
LangChain provides unique advantages when paired with 4D through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine 4D 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 4D queries for multi-turn workflows
4D + LangChain Use Cases
Practical scenarios where LangChain combined with the 4D MCP Server delivers measurable value.
RAG with live data: combine 4D tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query 4D, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain 4D tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every 4D tool call, measure latency, and optimize your agent's performance
4D MCP Tools for LangChain (6)
These 6 tools become available when you connect 4D to LangChain via MCP:
create_entity
Requires a JSON string representation of the data payload. Create a new record in the database
delete_entity
Delete a record from the database
get_catalog
Retrieve the database catalog definition
get_entity
Get a specific record by primary key
list_entities
Supports ORDA-style query parameters like $filter and $orderby for advanced lookups. Query records from a specific DataClass (table)
update_entity
Requires a JSON string payload. Update an existing record in the database
Example Prompts for 4D in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with 4D immediately.
"Show me the first 5 records from the 'Invoices' table."
"What tables (DataClasses) are exposed in my 4D catalog?"
"Create a new record in the 'Customers' table for 'John Doe' with email 'john@example.com'."
Troubleshooting 4D MCP Server with LangChain
Common issues when connecting 4D to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adapters4D + LangChain FAQ
Common questions about integrating 4D 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 4D 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 4D to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.