> This page is for version v2 API (default).
> For other versions, use one of these documentation indexes:
> - v2 API (default): https://docs.cohere.com/v2/llms.txt
> - v1 API: https://docs.cohere.com/v1/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.cohere.com/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.cohere.com/_mcp/server.

# MongoDB and Cohere (Integration Guide)

> Build semantic search and RAG systems using Cohere and MongoDB Atlas Vector Search.

![](/_fern-files/cohere.docs.buildwithfern.com/efabd5effbab706d3c0017470fe1fbc4f83cce9d27e574e7b516acfa9935c681/assets/images/f9726ea-mongo-db-logo.svg)

MongoDB Atlas Vector Search is a fully managed vector search platform from MongoDB. It can be used with Cohere's Embed and Rerank models to easily build semantic search or retrieval-augmented generation (RAG) systems with your data from MongoDB.

[This guide](https://www.mongodb.com/developer/products/atlas/how-use-cohere-embeddings-rerank-modules-mongodb-atlas/) walks through how to integrate Cohere models with MongoDB Atlas Vector Search.