• VECTOR DATA
  • RAG READY
  • SEMANTIC SEARCH
  • HUMAN REVIEW

How to generate embeddings for semantic search with your AI

Connect Mistral AI to your agent to turn text into vectors. Once linked, your AI can handle the math needed for semantic search.

Ask AI about this page

Short answer

How do I get embeddings from Mistral AI?

Your agent uses the generate_embeddings tool to convert text into numerical vectors. These vectors allow your AI to find relevant information based on meaning rather than just keywords. You'll get the math needed to populate a vector database.

The results of vectorization

What you get from your AI

These are the direct outputs after your agent processes your text.

VECTOR DATA

Numerical representations

The AI produces dense vectors for every text chunk. You get the exact numbers required to feed a vector database.

RAG READY

Context for retrieval

Your agent turns documents into searchable formats. This makes it easy to pull relevant facts during a conversation.

SEMANTIC SEARCH

Meaning-based matching

The AI finds content based on intent instead of keyword matching. This leads to much more accurate search results.

HUMAN REVIEW

Manual selection

You decide which specific text chunks are worth embedding. The AI won't pick and choose your source material for you.

The workflow

What your AI does when text arrives.

The AI handles the heavy lifting of vectorization so you don't have to write the math yourself.

  1. Input text

    You provide the raw text or documents you want to index. The AI prepares these strings for processing.

    generate_embeddings

  2. Vectorize content

    The AI converts the text into a list of numbers. This creates the semantic fingerprint for every chunk.

    generate_embeddings

  3. Format for storage

    The resulting embeddings are ready to be sent to your vector store. This prepares the data for immediate use in retrieval.

    generate_embeddings

  4. Verify results

    You check the output to ensure the vectors represent the text correctly. This step ensures your search stays accurate.

    generate_embeddings

Try it

Copy these to start.

Use these prompts to trigger the embedding process immediately.

Starting points

Replace the bracketed text with your actual file names or specific text snippets.

Mistral AI Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_RItYCqkPVcmlLP5CJAIJqs2Q9bmQGkYaBIA6d31x/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Mistral AI capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "mistral-ai-frontier-llms-embeddings-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_RItYCqkPVcmlLP5CJAIJqs2Q9bmQGkYaBIA6d31x/mcp"
    }
  }
}
Copy into chat04

  • Generate embeddings for the text in my 'project_notes.txt' file.

  • Create vectors for the customer feedback entries in this spreadsheet.

  • Use the generate_embeddings tool on the contents of the 'legal_docs' folder.

  • Convert this paragraph into an embedding so I can use it for semantic search.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Mistral AI once, then ask.

Link your account once. Your credentials stay encrypted, and you can start using the tools in any MCP-compatible client.

Connect Mistral AI to your AI

FAQ

How the embedding task behaves

  • 01

    Can the AI automatically delete my source files after embedding?

    No. The AI only reads the text to create embeddings. It has no permission to delete or modify your original files.

  • 02

    Does the AI store my embeddings for me?

    No. The AI generates the vectors, but you are responsible for saving them into your own vector database.

  • 03

    Can I use these embeddings for any model?

    The embeddings are generated by Mistral, so they are best used with models that support similar vector dimensions.

  • 04

    Will the AI choose which parts of my document to embed?

    No. You must tell the AI which specific text or files to process using the tools provided.

  • 05

    Can the AI perform the actual semantic search?

    The AI generates the vectors used for search. The actual matching and retrieval happen in your vector database or search engine.

  • More questions about Mistral AI? The Connector page answers them. See everything the Mistral AI Connector can do

Connect Mistral AI to Claude, Cursor, ChatGPT & more