Chroma
Summary
Chroma's official MCP server — build and query vector collections directly from an AI client.
Features
- Create collections and add documents from the assistant
- Semantic, keyword, and metadata-filtered queries
- Ephemeral, persistent, and cloud client modes
Installation
Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.
Description
Chroma's official MCP server exposes the whole embedding-database workflow to an assistant: create a collection, add documents, and query it, all without writing code.
What it exposes
- Collection management — create, list, inspect, and delete collections
- Document operations — add, update, and delete, with automatic embedding
- Querying by semantic similarity, full-text search, or metadata filter, and combinations of all three
- Client modes — ephemeral for throwaway work, persistent for a local directory, HTTP for a running server, and cloud for Chroma Cloud
Why this is useful in practice
It closes the loop on retrieval experiments. Instead of writing an ingestion script, running it, and then testing retrieval in another script, an assistant can add documents and immediately query them, iterating on chunking and metadata in one conversation.
It also works as a durable memory store: give the assistant a persistent collection and it can accumulate knowledge across sessions.
Setup
uvx chroma-mcp --client-type persistent --data-dir ./chroma, or with cloud credentials for a hosted collection.
Related MCP Servers
DBHub
by Bytebase
A universal database MCP server — one integration for PostgreSQL, MySQL, SQL Server, SQLite, and MariaDB.
MongoDB
by MongoDB
MongoDB's official MCP server — query databases, explore schemas, and manage Atlas clusters from an AI client.
Upstash Redis
by Upstash
Run Redis commands against Upstash's serverless Redis over HTTP, with documentation search built in.
dbt
by dbt Labs
dbt Labs' official MCP server — explore project metadata, run dbt commands, and query the Semantic Layer.