Together Embeddings

🌐Community
by zainhas · vlatest · Repository

Together Embeddings generates high-quality vector representations of text data for semantic search and AI applications, boosting performance & understanding.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add together-embeddings npx -- -y @trustedskills/together-embeddings
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "together-embeddings": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/together-embeddings"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

This skill provides access to Together AI's embedding models. Embeddings are numerical representations of text that capture semantic meaning, allowing for tasks like similarity search and clustering. You can use this skill to generate embeddings for text input, enabling your agent to understand relationships between different pieces of content.

When to use it

  • Semantic Search: Find documents or passages similar in meaning to a user's query.
  • Content Clustering: Group related articles or topics together based on their semantic similarity.
  • Recommendation Systems: Suggest relevant items (e.g., products, articles) based on the embeddings of previously viewed items.
  • Knowledge Base Indexing: Create an index for a knowledge base that allows for efficient retrieval of information based on meaning rather than keywords.

Key capabilities

  • Generates text embeddings using Together AI models.
  • Supports various input text lengths.
  • Provides numerical vector representations of text.

Example prompts

  • "Generate an embedding for the following sentence: 'The quick brown fox jumps over the lazy dog.'"
  • "Create embeddings for these two sentences and tell me how similar they are: 'I love pizza' and 'Pizza is my favorite food'."
  • “Embed this product description so I can find similar products.”

Tips & gotchas

  • The quality of the embeddings depends on the chosen Together AI model. Experiment with different models to find the best fit for your task.

Tags

🛡️

TrustedSkills Verification

Unlike other registries that point to live repositories, TrustedSkills pins every skill to a verified commit hash. This protects you from malicious updates — what you install today is exactly what was reviewed and verified.

Security Audits

Gen Agent Trust HubPass
SocketPass
SnykPass

Details

Version
vlatest
License
Author
zainhas
Installs
8

🌐 Community

Passed automated security scans.