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Chroma MCP Server

Chroma MCP Server

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github.com/privetinDatabases41Updated 95w ago

About Chroma MCP Server

Chroma MCP Server is an MCP server that provides vector database capabilities through Chroma. It supports document CRUD, semantic similarity search and metadata filtering, with data persisted in a local directory.

Key features

  1. 01Create, read, update and delete documents
  2. 02Semantic similarity search
  3. 03Metadata and content filtering
  4. 04Local persistent storage
  5. 05Automatic retries for transient failures

Use cases

  1. 01Running semantic search over a local document collection
  2. 02Adding a persistent document store to Claude Desktop
  3. 03Testing vector database operations with MCP Inspector

MCP support

Chroma MCP Server is an MCP server that exposes document management and similarity search tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Chroma MCP Server

A Model Context Protocol (MCP) server implementation that provides vector database capabilities through Chroma. This server enables semantic document search, metadata filtering, and document management with persistent storage.

Requirements

  • Python 3.8+
  • Chroma 0.4.0+
  • MCP SDK 0.1.0+

Components

Resources

The server provides document storage and retrieval through Chroma's vector database:

  • Stores documents with content and metadata
  • Persists data in src/chroma/data directory
  • Supports semantic similarity search
Tools

The server implements CRUD operations and search functionality:

Document Management
  • create_document: Create a new document

    • Required: document_id, content
    • Optional: metadata (key-value pairs)
    • Returns: Success confirmation
    • Error: Already exists, Invalid input
  • read_document: Retrieve a document by ID

    • Required: document_id
    • Returns: Document content and metadata
    • Error: Not found
  • update_document: Update an existing document

    • Required: document_id, content
    • Optional: metadata
    • Returns: Success confirmation
    • Error: Not found, Invalid input
  • delete_document: Remove a document

    • Required: document_id
    • Returns: Success confirmation
    • Error: Not found
  • list_documents: List all documents

    • Optional: limit, offset
    • Returns: List of documents with content and metadata
Search Operations
  • search_similar: Find semantically similar documents
    • Required: query
    • Optional: num_results, metadata_filter, content_filter
    • Returns: Ranked list of similar documents with distance scores
    • Error: Invalid filter

Features

  • Semantic Search: Find documents based on meaning using Chroma's embeddings
  • Metadata Filtering: Filter search results by metadata fields
  • Content Filtering: Additional filtering based on document content
  • Persistent Storage: Data persists in local directory between server restarts
  • Error Handling: Comprehensive error handling with clear messages
  • Retry Logic: Automatic retries for transient failures

Installation

  1. Install dependencies:
uv venv
uv sync --dev --all-extras

Configuration

Claude Desktop

Add the server configuration to your Claude Desktop config:

Windows: C:\Users\<username>\AppData\Roaming\Claude\claude_desktop_config.json

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "chroma": {
      "command": "uv",
      "args": [
        "--directory",
        "C:/MCP/server/community/chroma",
        "run",
        "chroma"
      ]
    }
  }
}
Data Storage

The server stores data in:

  • Windows: src/chroma/data
  • MacOS/Linux: src/chroma/data

Usage

  1. Start the server:
uv run chroma
  1. Use MCP tools to interact with the server:
# Create a document
create_document({
    "document_id": "ml_paper1",
    "content": "Convolutional neural networks improve image recognition accuracy.",
    "metadata": {
        "year": 2020,
        "field": "computer vision",
        "complexity": "advanced"
    }
})

# Search similar documents
search_similar({
    "query": "machine learning models",
    "num_results": 2,
    "metadata_filter": {
        "year": 2020,
        "field": "computer vision"
    }
})

Error Handling

The server provides clear error messages for common scenarios:

  • Document already exists [id=X]
  • Document not found [id=X]
  • Invalid input: Missing document_id or content
  • Invalid filter
  • Operation failed: [details]

Development

Testing
  1. Run the MCP Inspector for interactive testing:
npx @modelcontextprotocol/inspector uv --directory C:/MCP/server/community/chroma run chroma
  1. Use the inspector's web interface to:
    • Test CRUD operations
    • Verify search functionality
    • Check error handling
    • Monitor server logs
Building
  1. Update dependencies:
uv compile pyproject.toml
  1. Build package:
uv build

Contributing

Contributions are welcome! Please read our Contributing Guidelines for details on:

  • Code style
  • Testing requirements
  • Pull request process

License

This project is licensed under the MIT License - see the LICENSE file for details.

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