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
• Validation System: Evidence-based validation for code changes and learning promotions
• Automated Test-Driven Learning: Fully automated workflow from test failure to verified fix and learning promotion. See the Pytest Plugin Usage Guide to integrate this into your projects.

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
• Automatic Collection Creation: Essential collections (e.g., chat_history_v1, codebase_v1) are automatically created on server startup if they don't exist.
• 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

... View full README on GitHub