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Chroma MCP Server

Chroma MCP Server

Public
privetin/chroma

Provides Model Context Protocol-based vector database services with semantic document search, metadata and content filtering, persistent storage, and comprehensive CRUD operations for efficient document management.

python
0 tools
May 30, 2025
Updated Jun 4, 2025

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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\\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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