How to Use the NVIDIA API Catalog MCP in AutoGen

Q: How do I register the NVIDIA API Catalog tools with my AutoGen agents?

Install autogen-extmcp and pass your Vinkius MCP Server URL to the mcpservertools function. This automatically maps the tools to your AssistantAgent instances.

Q: Can AutoGen agents check endpoint latency using the NVIDIA API Catalog?

Yes. Your monitoring agent can run nvidiagetcloudstatus to check real-time latencies. If an endpoint is slow, the agent can notify the group to route requests elsewhere.

Q: How do AutoGen agents handle fine-tuned models from the NVIDIA API Catalog?

Agents can invoke nvidialistloraadapters to discover available fine-tuned overrides. They can then dynamically apply these adapters to their chat completion calls during the debate.

Q: Can agents summarize long discussions using this toolset?

Yes, agents can pass conversation logs to nvidiasummarizecontent. This is ideal for condensing long debates into a brief status update before saving the session state.

Build multi-agent debates where Nemotron and Llama3 models negotiate task execution with AutoGen.

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Connect NVIDIA API Catalog MCP to AutoGen

Create your Vinkius account to connect NVIDIA API Catalog to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup NVIDIA API Catalog with AutoGen

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Perplexity

Multi-agent consensus on chat completions

The `nvidia_chat_completion` tool processes natural language queries across hosted foundation models. In an AutoGen setup, one agent can generate a response using Nemotron, while a critic agent reviews it using Llama3. This collaborative feedback loop ensures high-quality outputs before delivering the final text. The agents negotiate and refine the response autonomously without requiring manual human oversight.

Budget-aware agent coordination

The `nvidia_check_token_quota` tool monitors your active credit limits and execution boundaries. This MCP tool allows your coordinator agent to verify remaining budget before delegating expensive tasks. If the quota drops below a specific threshold, the coordinator can switch the workflow to lighter models or halt execution. This prevents runaway loops from draining your API balance.

Multimodal validation in AutoGen MCP Server groups

The `nvidia_vision_inference` tool executes visual analysis on graphical data using Llama-Vision models. A design agent can pass an image to this tool, while a validation agent checks the output text for compliance. This enables complex visual QA pipelines where multiple agents debate the content of an image. You get a highly reliable analysis because the final decision requires consensus from the entire agent group.

Setup guide

Set up NVIDIA API Catalog MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes NVIDIA API Catalog tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="NVIDIA API Catalog_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent NVIDIA API Catalog data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="NVIDIA API Catalog_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent NVIDIA API Catalog data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NVIDIA API Catalog. 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.

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Common questions about NVIDIA API Catalog MCP in AutoGen

Install `autogen-ext[mcp]` and pass your Vinkius MCP Server URL to the `mcp_server_tools` function. This automatically maps the tools to your `AssistantAgent` instances.

Yes. Your monitoring agent can run `nvidia_get_cloud_status` to check real-time latencies. If an endpoint is slow, the agent can notify the group to route requests elsewhere.

Agents can invoke `nvidia_list_lora_adapters` to discover available fine-tuned overrides. They can then dynamically apply these adapters to their chat completion calls during the debate.

Yes, agents can pass conversation logs to `nvidia_summarize_content`. This is ideal for condensing long debates into a brief status update before saving the session state.

All configuration data and conversation logs are processed in memory within secure, ephemeral V8 isolates. No persistent storage is used, and the entire runtime environment is destroyed immediately after your agents finish their run.

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