Chroma
A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filterin
What is Chroma?
Chroma is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to server that provides data retrieval capabilities powered by chroma embedding database, enabling ai models to create collections over generated data and user inputs, and retrieve that data using vector...
A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filterin
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A server that provides data retrieval capabilities powered b
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx chroma-mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Chroma
Chroma MCP Server connects AI assistants to Chroma, an open-source embedding database, giving models the ability to create collections, add documents with vector embeddings, and retrieve them through semantic vector search, full-text search, and metadata filtering — all through natural language. It supports ephemeral in-memory storage, persistent local storage, and Chroma Cloud, making it suitable for everything from quick experiments to production knowledge bases that give your AI persistent memory.
Prerequisites
- Python 3.10 or later with uv or pip installed
- An MCP client such as Claude Desktop
- Optional: a Chroma Cloud account with tenant ID, database name, and API key for cloud storage
- Optional: API keys for embedding providers (Cohere, OpenAI, Jina, VoyageAI, Roboflow) if using non-default embeddings
Install Chroma MCP via uv (recommended)
uv is the recommended Python package runner. Install it with 'pip install uv' or via the uv installer script, then run the server.
uvx chroma-mcpChoose a client type
Select the storage backend by passing the --client-type flag. Options are ephemeral (default, in-memory), persistent (local disk), http (self-hosted Chroma server), or cloud (Chroma Cloud).
# Persistent local storage
uvx chroma-mcp --client-type persistent --data-dir /path/to/data
# Chroma Cloud
uvx chroma-mcp --client-type cloud --tenant <tenant-id> --database <db-name> --api-key <key>
# Self-hosted HTTP
uvx chroma-mcp --client-type http --host localhost --port 8000Configure Claude Desktop
Add the Chroma MCP block to your Claude Desktop configuration file with your chosen client type and credentials.
{
"mcpServers": {
"chroma": {
"command": "uvx",
"args": [
"chroma-mcp",
"--client-type", "persistent",
"--data-dir", "/Users/you/chroma-data"
]
}
}
}Set embedding provider API keys (optional)
If you want to use a non-default embedding model, set the provider's API key as an environment variable using the CHROMA_<PROVIDER>_API_KEY pattern.
export CHROMA_OPENAI_API_KEY=sk-...
export CHROMA_COHERE_API_KEY=...Create a collection and add documents
Ask Claude to create a named collection and add documents to it. Chroma will automatically generate embeddings for the content.
Query with semantic search
Ask Claude to retrieve relevant content from a collection using natural-language queries. Results are ranked by vector similarity.
Chroma Examples
Client configuration
Claude Desktop config using persistent local storage.
{
"mcpServers": {
"chroma": {
"command": "uvx",
"args": [
"chroma-mcp",
"--client-type", "persistent",
"--data-dir", "/Users/you/chroma-data"
]
}
}
}Prompts to try
Example queries once Chroma MCP is connected.
- "Create a collection called 'research-notes' and add the following text: ..."
- "Search the 'research-notes' collection for documents about machine learning"
- "List all collections in Chroma"
- "How many documents are in the 'research-notes' collection?"
- "Find documents in 'product-docs' where metadata category equals 'API' and content mentions authentication"Troubleshooting Chroma
uvx: command not found
Install uv first: 'pip install uv' or follow the uv quickstart at https://docs.astral.sh/uv/. Alternatively use 'pip install chroma-mcp' and then 'python -m chroma_mcp' as the command.
Cloud client fails to connect with authentication error
Double-check CHROMA_TENANT, CHROMA_DATABASE, and CHROMA_API_KEY values. These can be found in your Chroma Cloud dashboard. Alternatively pass them as CLI args: --tenant, --database, --api-key.
Embedding model returns an error about missing API key
Set the appropriate environment variable for your provider, e.g. CHROMA_OPENAI_API_KEY for OpenAI or CHROMA_COHERE_API_KEY for Cohere. The default embedding function requires no key; only switch providers if you explicitly configured one.
Frequently Asked Questions about Chroma
What is Chroma?
Chroma is a Model Context Protocol (MCP) server that server that provides data retrieval capabilities powered by chroma embedding database, enabling ai models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filterin It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Chroma?
Follow the installation instructions on the Chroma GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Chroma?
Chroma works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Chroma free to use?
Yes, Chroma is open source and available under the Apache 2.0 license. You can use it freely in both personal and commercial projects.
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Set Up Chroma in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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