NVIDIA AI MCP Server for LangChain 9 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect NVIDIA AI through the 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({
"nvidia-ai": {
"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 NVIDIA AI, 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 NVIDIA AI MCP Server
Connect NVIDIA AI to any AI agent and harness the power of GPU-accelerated foundation models — chat with Llama, generate embeddings, write code with CodeLlama, translate text, and perform complex reasoning through the NVIDIA API Catalog.
LangChain's ecosystem of 500+ components combines seamlessly with NVIDIA AI through native MCP adapters. Connect 9 tools via the 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
- Chat with LLMs — Access Llama 3.1, Mistral, Nemotron, and more via chat completions
- Generate Embeddings — Create vector embeddings for search and clustering
- Code Generation — Write code from natural language prompts using CodeLlama
- Summarization — Condense long documents into concise summaries
- Translation — Neural translation between dozens of languages
- Text-to-SQL — Convert natural language questions into SQL queries
- Sentiment Analysis — Analyze the emotional tone of text
- Complex Reasoning — Ask questions to the 405B-parameter reasoning model
The NVIDIA AI MCP Server exposes 9 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 NVIDIA AI to LangChain via MCP
Follow these steps to integrate the NVIDIA AI 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 9 tools from NVIDIA AI via MCP
Why Use LangChain with the NVIDIA AI MCP Server
LangChain provides unique advantages when paired with NVIDIA AI through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine NVIDIA AI 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 NVIDIA AI queries for multi-turn workflows
NVIDIA AI + LangChain Use Cases
Practical scenarios where LangChain combined with the NVIDIA AI MCP Server delivers measurable value.
RAG with live data: combine NVIDIA AI tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query NVIDIA AI, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain NVIDIA AI tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every NVIDIA AI tool call, measure latency, and optimize your agent's performance
NVIDIA AI MCP Tools for LangChain (9)
These 9 tools become available when you connect NVIDIA AI to LangChain via MCP:
analyze_sentiment
Analyze the sentiment of a text
ask_question
Optionally provide context for better answers. Ask a question to a powerful reasoning model (405B params)
chat_completion
Use "model" to specify which AI model (e.g., "meta/llama-3.1-70b-instruct", "mistralai/mistral-large"). Messages should be in OpenAI format: [{role: "user", content: "..."}]. Chat with an NVIDIA AI model (Llama, Mistral, etc)
generate_code
Specify language if needed. Generate code from a natural language prompt
get_embeddings
Model: "nvidia/nv-embed-v1". Generate vector embeddings from text
list_models
List all available AI models on the NVIDIA API Catalog
summarize_text
Summarize long text into a concise version
text_to_sql
Convert natural language to SQL query
translate_text
Translate text to another language
Example Prompts for NVIDIA AI in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with NVIDIA AI immediately.
"Generate Python code for a REST API with FastAPI."
"Translate 'Hello, how are you?' to Japanese."
"Summarize: The quarterly report shows revenue grew 15% YoY..."
Troubleshooting NVIDIA AI MCP Server with LangChain
Common issues when connecting NVIDIA AI to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersNVIDIA AI + LangChain FAQ
Common questions about integrating NVIDIA AI 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 NVIDIA AI 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 NVIDIA AI to LangChain
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.