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Chroma MCP Server: Enterprise Database & Scalable AI Solutions - MCP Implementation

Chroma MCP Server: Enterprise Database & Scalable AI Solutions

Empower your models with enterprise-grade database capabilities via MCP—streamlining Chroma deployments for scalable, reliable AI solutions." )

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About Chroma MCP Server

What is Chroma MCP Server: Enterprise Database & Scalable AI Solutions?

Chroma MCP Server is an advanced enterprise-grade database solution designed to power scalable AI applications. Built on the Anthropic MCP framework, it enables seamless integration of external data sources into large language models (LLMs) through standardized protocols. This server acts as a bridge between structured enterprise data and AI workloads, ensuring efficient query processing and context management for applications requiring real-time data enrichment.

How to Use Chroma MCP Server: Enterprise Database & Scalable AI Solutions?

Implementation follows these core steps:

  • Select deployment mode (ephemeral for testing, persistent for production, or cloud-managed infrastructure)
  • Configure authentication using environment variables or direct parameters
  • Define data schemas matching your application's context requirements
  • Integrate with LLM frameworks via standardized MCP API endpoints
  • Implement rate-limiting and access controls for enterprise-grade security

Chroma MCP Server Features

Key Features of Chroma MCP Server: Enterprise Database & Scalable AI Solutions?

Core capabilities include:

  • Multi-protocol support: Handles JSON, SQL, and custom data formats natively
  • Dynamic scaling: Auto-adjusts resource allocation based on query load patterns
  • End-to-end encryption: Secures data in transit and at rest through TLS 1.3 and AES-256
  • Context window optimization: Smart pruning algorithms maintain performance at scale
  • Compliance-ready logging: Auditable API interactions with timestamped metadata

Use Cases of Chroma MCP Server: Enterprise Database & Scalable AI Solutions?

Common applications include:

  • Knowledge graph enrichment for customer service chatbots
  • Document analysis pipelines for legal/financial compliance
  • Real-time inventory management for supply chain LLMs
  • Personalized recommendation engines with context-aware filtering
  • Multi-tenant data orchestration for SaaS AI platforms

Chroma MCP Server FAQ

FAQ from Chroma MCP Server: Enterprise Database & Scalable AI Solutions?

  • Q: How does scaling work in production environments?
    A: Automatic sharding distributes data across nodes based on query热度 and resource utilization metrics
  • Q: Can I use custom authentication mechanisms?
    A: Yes, through the --custom-auth-credentials parameter or JWT token injection
  • Q: What data retention guarantees exist?
    A: Persistent storage ensures 99.999% durability with automatic backups to configured storage buckets
  • Q: How are costs managed at scale?
    A: Fine-grained cost allocation tags track resource consumption per application tenant

Content

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

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
  • 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

  • create_collection
  • peek_collection
  • list_collections
  • get_collection_info
  • get_collection_count
  • modify_collection
  • delete_collection
  • add_documents
  • query_documents
  • get_documents

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"
    ]
}
  1. 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.

  1. 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.

  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:
"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:

# 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"

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