Chroma

Chroma

v0.2.6
vector-databaseembeddingsragchroma

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.

Any MCP-compatible agent

Most agents (Claude, Cursor, Windsurf, VS Code, and more) read a standard mcpServers configuration.

  1. Open your agent's MCP configuration file.
  2. Merge the snippet below into it.
  3. Restart the agent — the "Chroma" tools will be available.
{
  "mcpServers": {
    "chroma-mcp": {
      "command": "uvx",
      "args": [
        "chroma-mcp",
        "--client-type",
        "persistent",
        "--data-dir",
        "./chroma"
      ]
    }
  }
}

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.

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