Server spec
- Install
- See source repository
- Transport
- http
- Auth
- Not publicly specified
- Language
- Not publicly specified
- Tools exposed
- 6
- Official
- Community
Chroma is a Model Context Protocol (MCP) server that provides AI agents with access to a specialized database for embeddings and document storage. It enables efficient vector search and full-text retrieval, making it useful for applications requiring contextual memory or similarity-based lookup. The server fits into the MCP ecosystem by acting as a persistence layer for AI-generated data and queries. Developers working on AI agents that need scalable storage and retrieval of embeddings or documents would find Chroma relevant. Its open-source nature allows for customization but requires self-hosting and management.
Tools exposed
store_documentquery_embeddingsfull_text_searchlist_collectionsdelete_documentsupdate_embeddings
Resources
documentsembeddingscollections
Requirements
- Python 3.7+
- A running Chroma server instance
Use cases
Retrieving similar documents based on vector embeddingsStoring and searching large volumes of AI-generated contentEnhancing AI agents with contextual memory via document storage
Pros & cons
Pros
- Open-source and customizable
- Supports both vector and full-text search
- Designed for AI applications
Cons
- Requires setup and maintenance of the database server
- Performance may vary with scale
- Limited publicly available documentation on advanced features
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Chroma