ChromaDB-MCP: Vector Database Server for AI Tools

A Model Context Protocol (MCP) server that integrates ChromaDB's vector database capabilities with Claude Desktop and Cursor IDE, enabling AI tools to perform natural language queries over document collections.

Bridging AI and Knowledge Repositories

ChromaDB-MCP emerged from a simple observation: AI tools need context to be truly effective. While large language models possess impressive reasoning abilities, they often lack the specific knowledge needed for specialized tasks. This project bridges that gap by connecting AI tools to your document collections using semantic search.

The server enables your AI assistants to find information based on meaning rather than keywords. When Claude or Cursor needs to answer a question about your data, ChromaDB-MCP retrieves the most relevant documents and provides them as context. This grounds AI responses in your actual information, dramatically reducing hallucinations and improving answer quality.

What sets this project apart is its focus on privacy and simplicity. Unlike cloud-based solutions, ChromaDB-MCP runs entirely on your local machine, keeping your data under your control. The intuitive similarity metrics (0-100%) make it easy to understand search results, while the persistent SQLite backend ensures your document collections remain available across sessions.

Key Capabilities

ChromaDB-MCP seamlessly connects vector search technology with AI tools through several core capabilities:

Semantic Understanding enables natural language queries across your document collections, finding information based on meaning rather than exact keyword matches. The server handles document embedding, storage, and retrieval, presenting results with intuitive similarity scores.

Document Management provides complete control over your knowledge base with full CRUD operations. Add new documents, organize them into collections, attach rich metadata, and filter results based on custom criteria.

AI Integration offers out-of-the-box compatibility with Claude Desktop and Cursor IDE through the Model Context Protocol. This standardized interface enables AI tools to query your document collections and use the retrieved information to enhance their responses.

Real-World Applications

ChromaDB-MCP transforms how AI tools interact with your information across various scenarios:

When researching complex topics, the server helps AI assistants pull relevant insights from research papers, articles, and notes. For content creators, it organizes and retrieves information based on conceptual similarity rather than rigid folder structures.

Developers find particular value in code understanding tasks, where the server helps AI tools explore codebases and provide context-aware assistance. The system also serves as a conversational memory for AI assistants, enabling them to recall and reference previous interactions.

Looking Forward

The ChromaDB-MCP project continues to evolve with planned enhancements including advanced filtering capabilities, support for multiple embedding models, and performance optimizations for large collections. We're also expanding metadata search functionality and integration with additional AI tools to make vector search technology accessible to more applications.

Installation & Integration

Prerequisites

Python 3.12+
uv package manager (recommended) or pip

Setup

# Clone the repository
git clone https://github.com/HumainLabs/chromadb-mcp.git
cd chromadb-mcp

# Create and activate virtual environment
uv venv
# On Windows: .venv\Scripts\activate
# On Unix: source .venv/bin/activate

# Install dependencies
uv pip install -e .

Claude Desktop Integration

Add the server to your Claude Desktop configuration:

{
  "mcpServers": {
    "chroma": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/chromadb-mcp",
        "run",
        "chromadb-mcp"
      ]
    }
  }
}