Chroma MCP Server

What is Chroma MCP Server about?

Chroma MCP Server exposes Chroma's embedding database through the Model Context Protocol, enabling LLMs to create collections, add documents, and perform semantic or keyword queries without writing custom storage code.

How to use Chroma MCP Server?

1. Install the server (see repository README for Python installation; typically uvx chroma-mcp).
2. Configure the client via command‑line arguments or environment variables (CHROMA_CLIENT_TYPE, CHROMA_DATA_DIR, CHROMA_TENANT, etc.).
3. Run the server, e.g. uvx chroma-mcp --client-type persistent --data-dir /path/to/data.
4. Invoke the provided tools (chroma_create_collection, chroma_add_documents, chroma_query_documents, …) from an LLM integration or CLI.

Key Features of Chroma MCP Server

• Flexible client types: ephemeral (in‑memory), persistent (file‑based), HTTP (self‑hosted), cloud (Chroma Cloud).
• Collection management: create, list (with pagination), modify, delete, view stats, configure HNSW parameters, select embedding functions.
• Document operations: add with metadata/custom IDs, semantic query, advanced filtering, retrieve by IDs/filters, full‑text search, update, delete.
• Multiple embedding functions: default, Cohere, OpenAI, Jina, VoyageAI, Roboflow (environment‑variable API key handling).
• Tooling: dedicated MCP tools (chroma_list_collections, chroma_query_documents, etc.) for easy interaction.

Use Cases of Chroma MCP Server

• Memory for agentic LLMs – store conversation snippets and retrieve relevant context on‑the‑fly.
• Knowledge bases – index internal documents, FAQs, or codebases and let LLMs answer questions with up‑to‑date information.
• RAG pipelines – combine vector search with metadata filters to retrieve precise chunks for retrieval‑augmented generation.
• Prototype testing – use the ephemeral client for fast, sandboxed experiments without persisting data.
• Enterprise deployment – connect to a self‑hosted or cloud Chroma instance for scalable, secure production workloads.

FAQ from the Chroma MCP Server

Q: Do I need to set API keys for embedding services? A: Yes. Set CHROMA_<PROVIDER>_API_KEY (e.g., CHROMA_OPENAI_API_KEY) in a .env file or export it before starting the server.

Q: Can I switch embedding functions after a collection is created? A: The embedding function is persisted with the collection configuration; to change it you must create a new collection or re‑initialize with the desired function.

Q: How does pagination work for list operations? A: List tools accept limit and offset (or page/page_size) arguments; the server returns the requested slice of collections or documents.

Q: Is there a way to load environment variables from a custom path? A: Yes. Use --dotenv-path /custom/.env or set CHROMA_DOTENV_PATH.

Q: What storage backend does the persistent client use? A: It stores Chroma data files in the directory specified by CHROMA_DATA_DIR.

Chroma MCP Server

The Model Context Protocol (MCP) is an open protocol designed for effortless integration between LLM applications and external data sources or tools, offering a standardized framework to seamlessly provide LLMs with the context they require.

This server provides data retrieval capabilities powered by Chroma, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, metadata filtering, and more.

Features

• Flexible Client Types

  • Ephemeral (in-memory) for testing and development
  • Persistent for file-based storage
  • HTTP client for self-hosted Chroma instances
  • Cloud client for Chroma Cloud integration (automatically connects to api.trychroma.com)

• Collection Management

  • Create, modify, and delete collections
  • List all collections with pagination support
  • Get collection information and statistics
  • Configure HNSW parameters for optimized vector search
  • Select embedding functions when creating collections

• Document Operations

  • Add documents with optional metadata and custom IDs
  • Query documents using semantic search
  • Advanced filtering using metadata and document content
  • Retrieve documents by IDs or filters
  • Full text search capabilities

Supported Tools

• chroma_list_collections - List all collections with pagination support
• chroma_create_collection - Create a new collection with optional HNSW configuration
• chroma_peek_collection - View a sample of documents in a collection
• chroma_get_collection_info - Get detailed information about a collection
• chroma_get_collection_count - Get the number of documents in a collection
• chroma_modify_collection - Update a collection's name or metadata
• chroma_delete_collection - Delete a collection
• chroma_add_documents - Add documents with optional metadata and custom IDs
• chroma_query_documents - Query documents using semantic search with advanced filtering
• chroma_get_documents - Retrieve documents by IDs or filters with pagination
• chroma_update_documents - Update existing documents' content, metadata, or embeddings
• chroma_delete_documents - Delete specific documents from a collection

Embedding Functions

Chroma MCP supports several embedding functions: default, cohere, openai, jina, voyageai, and roboflow.

The embedding functions utilize Chroma's collection configuration, which persists the selected embedding function of a collection for retrieval. Once a collection is created using the collection configuration, on retrieval for future queries and inserts, the same embedding function will be used, without needing to specify the embedding function again. Embedding function persistance was added in v1.0.0 of Chroma, so if you created a collection using version <=0.6.3, this feature is not supported.

When accessing embedding functions that utilize external APIs, please be sure to add the environment variable for the API key with the correct format, found in Embedding Function Environment Variables

Usage with Claude Desktop

1. To add an ephemeral client, add the following to your claude_desktop_config.json file:

"chroma": {
    "command": "uvx",
    "args": [
        "chroma-mcp"
    ]
}

2. To add a persistent client, add the following to your claude_desktop_config.json file:

"chroma": {
    "command": "uvx",
    "args": [
        "chroma-mcp",
        "--client-type",
        "persistent",
        "--data-dir",
        "/full/path/to/your/data/directory"
    ]
}

This will create a persistent client that will use the data directory specified.

3. To connect to Chroma Cloud, add the following to your claude_desktop_config.json file:

"chroma": {
    "command": "uvx",
    "args": [
        "chroma-mcp",
        "--client-type",
        "cloud",
        "--tenant",
        "your-tenant-id",
        "--database",
        "your-database-name",
        "--api-key",
        "your-api-key"
    ]
}

This will create a cloud client that automatically connects to api.trychroma.com using SSL.

Note: Adding API keys in arguments is fine on local devices, but for safety, you can also specify a custom path for your environment configuration file using the --dotenv-path argument within the args list, for example: "args": ["chroma-mcp", "--dotenv-path", "/custom/path/.env"].

4. To connect to a [self-hosted Chroma instance on your own cloud provider](https://docs.trychroma.com/ production/deployment), add the following to your claude_desktop_config.json file:

"chroma": {
    "command": "uvx",
    "args": [
      "chroma-mcp", 
      "--client-type", 
      "http", 
      "--host", 
      "your-host", 
      "--port", 
      "your-port", 
      "--custom-auth-credentials",
      "your-custom-auth-credentials",
      "--ssl",
      "true"
    ]
}

This will create an HTTP client that connects to your self-hosted Chroma instance.

Demos

Find reference usages, such as shared knowledge bases & adding memory to context windows in the Chroma MCP Docs

Using Environment Variables

You can also use environment variables to configure the client. The server will automatically load variables from a .env file located at the path specified by --dotenv-path (defaults to .chroma_env in the working directory) or from system environment variables. Command-line arguments take precedence over environment variables.

# Common variables
export CHROMA_CLIENT_TYPE="http"  # or "cloud", "persistent", "ephemeral"

# For persistent client
export CHROMA_DATA_DIR="/full/path/to/your/data/directory"

# For cloud client (Chroma Cloud)
export CHROMA_TENANT="your-tenant-id"
export CHROMA_DATABASE="your-database-name"
export CHROMA_API_KEY="your-api-key"

# For HTTP client (self-hosted)
export CHROMA_HOST="your-host"
export CHROMA_PORT="your-port"
export CHROMA_CUSTOM_AUTH_CREDENTIALS="your-custom-auth-credentials"
export CHROMA_SSL="true"

# Optional: Specify path to .env file (defaults to .chroma_env)
export CHROMA_DOTENV_PATH="/path/to/your/.env" 

Embedding Function Environment Variables

When using external embedding functions that access an API key, follow the naming convention CHROMA_<>_API_KEY="<key>". So to set a Cohere API key, set the environment variable CHROMA_COHERE_API_KEY="". We recommend adding this to a .env file somewhere and using the CHROMA_DOTENV_PATH environment variable or --dotenv-path flag to set that location for safekeeping.