> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.cohere.com/v2/docs/integrations/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.cohere.com/_mcp/server.

# Integrating Embedding Models with Other Tools

> Learn how to integrate Cohere embeddings with open-source vector search engines for enhanced applications.

Cohere supports integrations with a variety of powerful external platforms, which are covered in this section. Find links to specific guides below:

1. [Elasticsearch and Cohere](/docs/elasticsearch-and-cohere)
2. [MongoDB and Cohere](/docs/mongodb-and-cohere)
3. [Redis and Cohere](/docs/redis-and-cohere)
4. [Haystack and Cohere](/docs/haystack-and-cohere)
5. [Open Search and Cohere](/docs/opensearch-and-cohere)
6. [Vespa and Cohere](/docs/vespa-and-cohere)
7. [Chroma and Cohere](/docs/chroma-and-cohere)
8. [Qdrant and Cohere](/docs/qdrant-and-cohere)
9. [Weaviate and Cohere](/docs/weaviate-and-cohere)
10. [Pinecone and Cohere](/docs/pinecone-and-cohere)
11. [Milvus and Cohere](/docs/milvus-and-cohere)

> Cohere's API documentation helps developers easily integrate natural language processing and generation into their products.

## Docs

- [Elasticsearch and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/elasticsearch-and-cohere.md): Learn how to create a semantic search pipeline with Elasticsearch and Cohere's generative AI capabilities.
- [MongoDB and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/mongodb-and-cohere.md): Build semantic search and RAG systems using Cohere and MongoDB Atlas Vector Search.
- [Redis and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/redis-and-cohere.md): Learn how to integrate Cohere with Redis for similarity searches on text data with this step-by-step guide.
- [Haystack and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/haystack-and-cohere.md): Build custom LLM applications with Haystack, now integrated with Cohere for embedding, generation, chat, and retrieval.
- [Pinecone and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/pinecone-and-cohere.md): This page describes how to integrate Cohere with the Pinecone vector database.
- [Weaviate and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/weaviate-and-cohere.md): This page describes how to integrate Cohere with the Weaviate database.
- [Open Search and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/opensearch-and-cohere.md): Unlock the power of search and analytics with OpenSearch, enhanced by ML connectors like Cohere and Amazon Bedrock.
- [Vespa and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/vespa-and-cohere.md): This page describes how to integrate Cohere with the Vespa database.
- [Qdrant and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/qdrant-and-cohere.md): This page describes how to integrate Cohere with the Qdrant vector database.
- [Milvus and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/milvus-and-cohere.md): This page describes integrating Cohere with the Milvus vector database.
- [Zilliz and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/zilliz-and-cohere.md): This page describes how to integrate Cohere with the Zilliz database.
- [Chroma and Cohere (Integration Guide)](https://docs.cohere.com/v2/docs/chroma-and-cohere.md): This page describes how to integrate Cohere and Chroma.