NVIDIA API Catalog Connector for AI agents.
8 live capabilities
Deploy production-ready inference on NVIDIA's cloud compute matrix.
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Why people use NVIDIA API Catalog
NVIDIA API Catalog for Managing High-Scale Inference
With this Connector, your agent handles the heavy lifting. You just ask for a completion or a summary, and it navigates the NVIDIA cloud matrix for you. You get direct answers and clean data arrays without ever touching a configuration file.
What Vinkius changes
You get a direct bridge to NVIDIA's infrastructure without the overhead of manual SDK mapping.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Testing model variety
An engineer needs to see which models are live.
- Real-world use case 02
Building a RAG system
A developer needs to turn a library of PDFs into vectors.
- Real-world use case 03
Monitoring production health
An ops person wants to ensure low latency.
Complete set · 8capabilities
The complete NVIDIA API Catalog capability set.
These are the exact actions your AI can choose when you ask it to work with NVIDIA API Catalog.
01—04
4 capabilities in this set.
Part of 8 available through NVIDIA API Catalog.
- 01 Capability
Nvidia chat completion
Get direct NLP responses from hosted LLMs. This is useful for building chat interfaces with production-grade models.
- 02 Capability
Nvidia check token quota
See your current credit limits and execution constraints. Use this to prevent hitting unexpected limits during batch jobs.
- 03 Capability
Nvidia generate embeddings
Convert unstructured text into numerical arrays for your vector database. It helps build RAG pipelines efficiently.
- 04 Capability
Nvidia get cloud status
Check the health and latency of the NVIDIA cloud matrix. This helps you monitor your production environment's health.
05—08
4 capabilities in this set.
Part of 8 available through NVIDIA API Catalog.
- 05 Capability
Nvidia list foundation models
See a full list of available foundation models. This lets you quickly discover which models are currently hosted.
- 06 Capability
Nvidia list lora adapters
Find and track fine-tuned model overrides. It helps you manage specific fine-tuned versions of models.
- 07 Capability
Nvidia summarize content
Compress long text into clean, structured arrays. Use this to handle large-scale content summarization tasks.
- 08 Capability
Nvidia vision inference
Perform multimodal inference on images and graphical data. This allows your agent to process visual information.
Set up in minutes
One URL. Then ask NVIDIA API Catalog to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use NVIDIA API Catalog from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it NVIDIA API Catalog, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable NVIDIA API Catalog for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the NVIDIA API Catalog URL.
- Step 03
Save and start
Save the connection and enable NVIDIA API Catalog in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"nvidia-api-catalog": {
"url": "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using NVIDIA API Catalog
Open Agent mode in chat and ask: "Using NVIDIA API Catalog, help me...". 8 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"nvidia-api-catalog": {
"url": "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using NVIDIA API Catalog
Ask Copilot: "Using NVIDIA API Catalog, help me...". 8 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"nvidia-api-catalog": {
"url": "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using NVIDIA API Catalog
Open Cascade and ask: "Using NVIDIA API Catalog, help me...". 8 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"nvidia-api-catalog": {
"url": "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using NVIDIA API Catalog
Ask Cline: "Using NVIDIA API Catalog, help me...". 8 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add nvidia-api-catalog --transport http "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using NVIDIA API Catalog
Ask Claude: "Using NVIDIA API Catalog, show me...". 8 tools are ready
Where the request belongs
Work NVIDIA API Catalog can move forward.
The ML engineer who's tired of manual SDK configuration for every new model. The generative AI developer who needs to scale inference across a production cloud matrix without the headache of manual routing.
ML Engineer
Testing different foundation models to see which one handles your specific data best on a Tuesday afternoon.
AI Developer
Building a production app that needs to switch between Llama3 and Nemotron based on cost or speed.
Generative AI Integrator
Mapping out embeddings for a large-scale RAG system using NVIDIA's cloud compute.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsNVIDIA AI
Access LLMs, embeddings, code generation, and reasoning via NVIDIA API Catalog.
TrueFoundry
Universal LLM Gateway & ML deployment hub: invoke 1000+ proxy models and manage MCP service instances natively.
Groq
Run large language models at unprecedented speed with custom LPU hardware that delivers real-time AI inference at massive scale.
LiteLLM (LLM Proxy & Spend Tracking)
Manage your LLM gateway via LiteLLM. generate API keys, track spending, and orchestrate model fallback paths.
Cerebras Inference
Access lightning-fast AI inference via Cerebras Wafer-Scale Engine. generate chat completions, manage models, and run batch jobs at record speeds.
SambaNova (AI Inference)
High-speed AI inference for Llama 3, DeepSeek, and MiniMax models via SambaNova's ultra-fast SN40L chips.
Bring your own AI
Change the model, client or framework. Keep NVIDIA API Catalog connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about NVIDIA API Catalog.
The practical details behind the request, access and result.
Can I use the NVIDIA API Catalog MCP to access Llama3?
Yes, this Connector gives your agent direct access to Llama3 and other foundation models hosted on NVIDIA's cloud infrastructure.
How does the NVIDIA API Catalog MCP help with my token limits?
It allows your agent to check your current credit status and execution constraints in real-time, helping you manage your budget.
Does the NVIDIA API Catalog MCP support vision tasks?
Yes, it includes capabilities to run multimodal inference on images and graphical data, letting your agent see and analyze visual information.
Can I use NVIDIA API Catalog MCP to manage my LoRA adapters?
Yes, you can use it to find and track specific fine-tuned overrides and adapters available within the NVIDIA catalog.
How do I check if the NVIDIA cloud models are currently online?
The Connector can ping the core hosted matrix to check for latencies and ensure the endpoints are healthy before you send a request.
Can the NVIDIA API Catalog MCP help me create embeddings for my data?
Yes, it provides a way to convert your unstructured text into numerical arrays, which is perfect for building a vector database.
Can I explicitly route specific embedding vectors natively using the NVIDIA integration matrix?
Yes! Utilize generate_embeddings providing explicit logic extracting arrays natively isolating endpoints safely.
How do I explicitly explore active LLMs natively hosted inside the NVIDIA catalog bounds?
Target explicit matrices natively calling list_foundation_models returning catalog endpoints safely explicitly mapping bounds secure natively.
Does this require local Docker execution mapping explicitly NVIDIA parameters transparently?
No, this explicitly pings the hosted Cloud API. For local Docker metrics natively, switch to nvidia-nim-mcp enforcing natively local boundaries.
One connection away
Give your agent a direct line to NVIDIA API Catalog.
Connect NVIDIA API Catalog once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available