- VECTOR
- DATABASE
- SEARCH
- HUMAN
Short answer
How do I turn text into embeddings?
Your agent sends text to the NVIDIA API to get high-dimensional numerical arrays. These vectors represent semantic meaning, which you can then use for similarity searches or to populate a vector database.
The results
Where your data lands
The process converts raw text into usable mathematical representations.
VECTOR
Numerical arrays
The AI produces dense vectors that capture the semantic context of your input text.
DATABASE
Vector storage
You get the arrays needed to fill up vector databases for long-term storage.
SEARCH
Semantic retrieval
These embeddings let your agent find information based on meaning instead of just matching keywords.
HUMAN
Manual selection
You decide which specific text chunks are worth vectorizing and how to organize your final index.
The workflow
What your AI does when text arrives.
The AI acts as the bridge between your raw text and the math required for semantic search.
Text ingestion
Your agent reads the raw text from the documents or logs you want to process.
nvidia_generate_embeddingsVectorization
The AI converts those text segments into precise numerical arrays via the NVIDIA API.
nvidia_generate_embeddingsData formatting
The agent organizes the resulting vectors into a format your database can accept.
nvidia_generate_embeddingsDimension check
The AI verifies the output dimensions to ensure they match your target vector store.
nvidia_generate_embeddings
Try it
Copy these to start.
Use these prompts to begin the embedding process.
Starting points
Swap the bracketed text for your actual file names or database names.
NVIDIA API Catalog Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — NVIDIA API Catalog capabilities are ready to use.
{
"mcpServers": {
"nvidia-api-catalog-mcp": {
"url": "https://edge.vinkius.com/vk_preview_LgfbZayzkE3ZBfq9HWv3rgeK69AXP0h3anUpakUy/mcp"
}
}
}Generate embeddings for the text in [document.txt] and prepare them for my vector store.
Convert the latest entries in [database_table] into numerical vectors.
Take these support logs from [folder_path] and create embeddings for semantic search.
Embed the content of [file_name] so I can perform similarity lookups.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect NVIDIA API Catalog once, then ask.
Link your account once. Your credentials stay encrypted on our side, and you can immediately start asking your agent to vectorize data.
Connect NVIDIA API Catalog to your AIFAQ
How this task behaves
- 01
Can the AI automatically update my vector database?
No. The AI generates the embeddings, but you must use your own tools to write those vectors into your database.
- 02
Does the AI store my raw text?
No. The AI sends the text to the API to get the math, but it doesn't keep a permanent copy of your data.
- 03
Can I choose the embedding model?
The AI uses the specific models provided through the NVIDIA API Catalog tools.
- 04
Will the AI delete my original files?
No. The AI only reads the text to create embeddings; it has no capability to delete or modify your source files.
- 05
Can it embed images?
No. This tool is specifically for converting text into numerical arrays.
More questions about NVIDIA API Catalog? The Connector page answers them. See everything the NVIDIA API Catalog Connector can do
Connect NVIDIA API Catalog to Claude, Cursor, ChatGPT & more
