Chroma MCP Server

A Model Context Protocol (MCP) server integration for Chroma, the open-source embedding database.

Overview

Chroma MCP Server creates a persistent, searchable “working memory” for AI-assisted development:

• Automated Context Recall: AI assistants can query relevant information from past sessions
• Developer-Managed Persistence: Store key decisions and insights in ChromaDB via MCP
• Second Brain Integration: Integrates with IDE workflows to create a unified knowledge hub

Key features:

• Automated Codebase Indexing: Track and index code changes
• Automated Chat Logging: Log AI interactions with enhanced context capture (code diffs, tool sequences)
• Bidirectional Linking: Connect discussions to code changes for tracing feature evolution
• Semantic Code Chunking: Preserve logical code structures for more meaningful context retrieval
• Working Memory Tools: MCP commands for capturing and retrieving development context

See the Getting Started with your Second Brain guide for more details.

Quick Start

Installation

# Basic installation
pip install chroma-mcp-server

# Full installation with all embedding models
pip install "chroma-mcp-server[full]"

Running

# With in-memory storage (data lost on restart)
chroma-mcp-server --client-type ephemeral

# With persistent storage
chroma-mcp-server --client-type persistent --data-dir ./my_data

Cursor Integration

Add or modify .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "chroma": {
      "command": "uvx",
      "args": [
        "chroma-mcp-server"
      ],
      "env": {
        "CHROMA_CLIENT_TYPE": "persistent",
        "CHROMA_DATA_DIR": "/path/to/your/data",
        "CHROMA_LOG_DIR": "/path/to/your/logs",
        "LOG_LEVEL": "INFO",
        "MCP_LOG_LEVEL": "INFO",
        "MCP_SERVER_LOG_LEVEL": "INFO"
      }
    }
  }
}

Recent Improvements

• Enhanced Context Capture: Automatically extracts code diffs, tool sequences, and assigns confidence scores
• Bidirectional Linking: Creates navigable connections between chat discussions and code changes
• Semantic Code Chunking: Uses logical boundaries (functions, classes) instead of fixed-size chunks
• Server-Side Timestamp Enforcement: Ensures consistent timestamps across all collections
• Enhanced Logging System: Per-execution log files prevent contamination of JSON communication in stdio mode
• Embedding Function Management: Tools to update collection metadata when changing embedding functions
• Collection Setup Command: Simplifies creation of multiple collections with consistent configuration
• Auto-Promote Workflow: Streamlined derived learning promotion with automatic handling of high-confidence entries
• Smart Defaults: Interactive promotion with intelligent defaults for all fields based on context
• Low Confidence Warnings: Visual indicators for entries that may need more careful review

Documentation

Comprehensive documentation is available in the docs directory:

• Main Documentation - Complete guide to installation, configuration, and usage
• Getting Started - Detailed setup instructions
• Developer Guide - For contributors and developers
• Server Logging - Details on the improved logging system
• Enhanced Context Capture - Details on code diff extraction and tool sequencing
• Semantic Code Chunking - Logic-preserving code chunking for meaningful retrieval
• Automated Chat Logging - Enriched chat history with bidirectional linking
• API Reference - Available MCP tools and parameters

License

MIT License (see LICENSE)