• VECTORIZED
  • RANKED
  • ACCURATE
  • HUMAN

How to build advanced search systems with your AI

Connect Together AI to your agent to turn raw text into a precise retrieval engine. Once connected, your AI handles the heavy lifting of finding and ranking data.

Ask AI about this page

Short answer

How do I make my AI's search more accurate?

You use Together AI to convert your documents into mathematical vectors and then re-order the results based on relevance. This two-step process ensures your agent finds the right context instead of just matching keywords. You'll see how the math turns into better answers below.

Search outcomes

Where your data lands.

This process moves your data from raw text to ranked intelligence.

VECTORIZED

Searchable data maps

The AI converts your text into embeddings. This allows your agent to understand meaning rather than just looking for exact word matches.

RANKED

Top-tier relevance

Reranking puts the most useful documents at the top of the list. Your agent gets the best context first, which stops it from hallucinating.

ACCURATE

High-precision retrieval

By combining vector math with reranking, you get a system that actually understands your specific domain. The results stay relevant to your questions.

HUMAN

Manual review needed

You still need to check the final answers. The AI finds the data, but you decide if the logic holds up for your specific use case.

The workflow

What your AI does when the data arrives.

The AI follows a specific pipeline to turn your files into a searchable brain.

  1. Vectorize the text

    Your agent turns your raw documents into numerical representations. This makes the content searchable by concept.

    create_embeddings

  2. Find matches

    The system scans your existing vector database to pull out the most likely candidates for a query.

    create_embeddings

  3. Refine the list

    The AI looks at the initial matches and re-orders them to ensure the most important information is at the very top.

    create_rerank

  4. Deliver context

    The most relevant snippets are handed to your agent to answer your question.

    create_rerank

Try it

Copy these to start.

Use these prompts to trigger the search workflow immediately.

Starting points

These are starting points. Swap out the bracketed text with your actual file names or folder paths.

Together AI Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/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 — Together AI capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "together-ai-alternative-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_3DCNpnHYF8hhWcXn2SCKuEfpGwWZe18MoQz7sb18/mcp"
    }
  }
}
Copy into chat04

  • Create embeddings for my technical documentation folder.

  • Rerank these search results to find the most relevant section in the user manual.

  • Use the embeddings from my project notes to find everything related to the API migration.

  • Rerank the top 10 documents from my legal folder to find the specific clause on liability.

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

Start here

Connect Together AI once, then ask.

Just click the link to connect your account. Your credentials stay encrypted, and you can start searching your data through your preferred AI client right away.

Connect Together AI to your AI

FAQ

How the search behaves

  • 01

    Can the AI delete my original documents?

    No. This MCP only reads and processes data to create embeddings and rerank results. It cannot modify or delete your files.

  • 02

    Does it search my entire hard drive?

    No. It only processes the specific files or folders you direct it to via your prompts.

  • 03

    How does reranking help my agent?

    Reranking takes the broad matches found during the embedding search and sorts them so the most contextually relevant information is presented first.

  • 04

    Can the AI write new documents for me?

    No. The tools in this MCP are strictly for retrieval and ranking. Writing or creating new files is a task for your AI client, not this connector.

  • 05

    Do I need to manage the vector database myself?

    No. The AI uses the create_embeddings tool to handle the mathematical representation of your data automatically.

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

Connect Together AI to Claude, Cursor, ChatGPT & more