• PRECISION
  • UNDERSTANDING
  • RELIABILITY
  • HUMAN

How to optimize semantic search results with your AI

Connect Cohere to your AI client to fix retrieval issues. Your agent will pull the most relevant context from your documents without getting lost in the noise.

Ask AI about this page

Short answer

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

You use embeddings to turn text into vectors that represent meaning, then use reranking to sort the best matches to the top. This ensures your agent sees the most useful information first. You'll get much higher precision in your retrieval pipelines.

The results you get.

Where your data lands.

This setup changes how your agent handles your documents.

PRECISION

Relevant context first

The agent sorts the best matches to the top. You get the most useful information immediately.

UNDERSTANDING

Meaning over keywords

The agent finds answers based on intent. It understands the concept instead of just matching words.

RELIABILITY

Fewer hallucinations

When the agent gets the right context, it stops making things up. You get more accurate answers.

HUMAN

Manual oversight

You still decide which documents to index or which results are actually correct. The AI just does the sorting.

The workflow

What your AI does when the data arrives.

The agent moves from raw text to a ranked list of high-quality context.

  1. Vectorize text

    The agent turns your document chunks into vectors that capture semantic meaning. This makes the data searchable by concept.

    embed

  2. Find candidates

    The agent performs a fast search across the vector space to find a broad set of potentially relevant documents.

    embed

  3. Reorder results

    The agent takes the initial list and runs a more intensive check to see which documents actually match the query.

    rerank

  4. Deliver context

    The most relevant pieces of information are handed to the agent to use for its final response.

    rerank

Try it

Copy these to start.

Use these prompts to begin working with your data.

Starting points

These are opening lines. Swap out the specific file names or folder paths for your own.

Cohere Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_R4ERIik35jE1vo5hRbvNHBrwGzLbWOtl3sZQNmPU/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 — Cohere capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "cohere-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_R4ERIik35jE1vo5hRbvNHBrwGzLbWOtl3sZQNmPU/mcp"
    }
  }
}
Copy into chat04

  • Embed these technical manuals from my local folder so I can ask questions about them.

  • Rerank the search results from my product documentation to find the most relevant troubleshooting steps.

  • Use the embedding tool to help me find all documents in my project folder related to user authentication.

  • Rerank these retrieved snippets from my knowledge base to prioritize the most recent policy updates.

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

Start here

Connect Cohere once, then ask.

Link your account once. Your credentials stay encrypted, and you can immediately start using these tools in your favorite AI client.

Connect Cohere to your AI

FAQ

How this task behaves.

  • 01

    Can the AI change my original documents?

    No. The tools only read and process data to create embeddings or rank results. Your source files remain untouched.

  • 02

    Does the AI delete any of my data?

    No. This MCP does not have any tools for deleting or modifying your files.

  • 03

    What is the difference between embedding and reranking?

    Embedding is for finding a large group of potentially relevant items quickly. Reranking is for looking closely at those items to put the best ones at the top.

  • 04

    Do I need to manage a vector database?

    No. The tools handle the mathematical processing, but you still manage where your data lives.

  • 05

    Can I use this with any AI client?

    Yes, as long as your client supports the Model Context Protocol.

  • More questions about Cohere? See everything the Cohere Connector can do

Connect Cohere to Claude, Cursor, ChatGPT & more