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  3. Chroma MCP
Chroma MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 2:47:03 PM

Chroma MCP

User RatingsBe the first to rate and review this MCP server!
View Repository591 GitHub StarsTotal stargazers on GitHub for the source repository (591 stars).Visit Website
databasevector-searchembeddingmcpchroma

MCP server providing vector and full-text search over local or cloud Chroma embedding database instances.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Automated check passed— started and listed 13 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON ā–¾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "chroma-core-chroma-mcp": {
      "command": "uvx",
      "args": [
        "chroma-mcp"
      ]
    }
  }
}

šŸ’” Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (13) Directory Badge Claim listing AlternativesšŸ—„ļø More in Databases

Overview

This server enables AI applications to interact with Chroma embedding databases for storing and retrieving documents using vector search, full-text search, and metadata filtering. It supports ephemeral in-memory, persistent file-based, HTTP, and cloud clients, allowing flexible deployment options. Use it to manage collections and documents with advanced search capabilities in self-hosted or Chroma Cloud environments.

Use cases

•Create and manage embedding collections with custom configurations
•Add, update, and delete documents with metadata and embeddings
•Perform semantic vector searches with filtering and pagination
•Retrieve documents by ID or metadata filters
•Integrate with local or cloud-hosted Chroma instances for AI context retrieval

Key features

•Supports ephemeral, persistent, HTTP, and cloud client types
•Collection management with create, modify, delete, and info retrieval
•Document operations including add, query, update, delete, and full-text search
•Configurable HNSW parameters for vector search optimization
•Supports multiple embedding functions with persistence per collection

Capabilities & Tool Schemas (13) ~2.8k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Chroma MCP.

chroma_list_collections

List all collection names in the Chroma database with pagination support. Args: limit: Optional maximum number of collections to return offset: Optional number of collections to skip before returning results Returns: List of collection names or ["__NO_COLLECTIONS_FOUND__"] if database is empty

chroma_create_collection

Create a new Chroma collection with configurable HNSW parameters. Args: collection_name: Name of the collection to create embedding_function_name: Name of the embedding function to use. Options: 'default', 'cohere', 'openai', 'jina', 'voyageai', 'ollama', 'roboflow' metadata: Optional metadata dict to add to the collection

chroma_peek_collection

Peek at documents in a Chroma collection. Args: collection_name: Name of the collection to peek into limit: Number of documents to peek at

chroma_get_collection_info

Get information about a Chroma collection. Args: collection_name: Name of the collection to get info about

chroma_get_collection_count

Get the number of documents in a Chroma collection. Args: collection_name: Name of the collection to count

chroma_modify_collection

Modify a Chroma collection's name or metadata. Args: collection_name: Name of the collection to modify new_name: Optional new name for the collection new_metadata: Optional new metadata for the collection

Documentation Overview

Chroma logo

Chroma - the open-source embedding database.
The fastest way to build Python or JavaScript LLM apps with memory!

Discord | License | Docs | Homepage

Chroma MCP Server

smithery badge

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.

This is a MCP server for self-hosting your access to Chroma. If you are looking for Package Search you can find the repository for that here.

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:
json
"chroma": {
    "command": "uvx",
    "args": [
        "chroma-mcp"
    ]
}
  1. To add a persistent client, add the following to your claude_desktop_config.json file:
json
"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.

  1. To connect to Chroma Cloud, add the following to your claude_desktop_config.json file:
json
"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"].

  1. 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:
json
"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.

server.ts
# 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.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
591
Stargazers on the source repository.
Last commit
11mo ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
13
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Chroma MCP

It supports ephemeral (in-memory), persistent (file-based), HTTP, and cloud clients for flexible deployment.

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Technical Specs & Signals

CategoryšŸ—„ļøDatabases
PricingFree
More technical detailsExpand ā–¾
TransportSTDIO
RuntimePython
AuthAPI key
LicenseApache-2.0
ClientsClaude Desktop
Last updatedAug 9, 2026
11/11 checks healthy over the last 33d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars591
GitHub Star CountTotal stargazers on GitHub representing community popularity (591 stars).
Last commit11mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 17, 2025
71Quality signal: Great Ā· 71/100How this signal is calculated ā–¾
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity6/15
Community engagement0/10

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Scanned 23d ago via OSV.dev Ā· chroma-mcp (PyPI)

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