NVIDIA AI MCP Server for AutoGen 9 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add NVIDIA AI as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="nvidia_ai_agent",
tools=tools,
system_message=(
"You help users with NVIDIA AI. "
"9 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use NVIDIA AI tools. Connect 9 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
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 AutoGen 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 AutoGen via MCP
Follow these steps to integrate the NVIDIA AI MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 9 tools from NVIDIA AI automatically
Why Use AutoGen with the NVIDIA AI MCP Server
AutoGen provides unique advantages when paired with NVIDIA AI through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use NVIDIA AI tools to solve complex tasks
Role-based architecture lets you assign NVIDIA AI tool access to specific agents — a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive NVIDIA AI tool calls
Code execution sandbox: AutoGen agents can write and run code that processes NVIDIA AI tool responses in an isolated environment
NVIDIA AI + AutoGen Use Cases
Practical scenarios where AutoGen combined with the NVIDIA AI MCP Server delivers measurable value.
Collaborative analysis: one agent queries NVIDIA AI while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from NVIDIA AI, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using NVIDIA AI data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process NVIDIA AI responses in a sandboxed execution environment
NVIDIA AI MCP Tools for AutoGen (9)
These 9 tools become available when you connect NVIDIA AI to AutoGen 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 AutoGen
Ready-to-use prompts you can give your AutoGen 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 AutoGen
Common issues when connecting NVIDIA AI to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"NVIDIA AI + AutoGen FAQ
Common questions about integrating NVIDIA AI MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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 AutoGen
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.