
djm81/chroma_mcp_server
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MCP Server for ChromaDB integration into Cursor with MCP compatible AI models
概要
A Model Context Protocol (MCP) server integration for Chroma, the open-source embedding database. Chroma MCP Server creates a persistent, searchable "working memory" for AI-assisted development: - AI assistants can query relevant information from past sessions - Store key decisions and insights in ChromaDB via MCP - Integrates with IDE workflows to create a unified knowledge hub - Track and index code changes - Log AI interactions with enhanced context capture (code diffs, tool sequences) - Connect discussions to code changes for tracing feature evolution - Preserve logical code structures for more meaningful context retrieval - MCP commands for capturing and retrieving development context - Evidence-based validation for code changes and learning promotions - 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.
README
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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
インストール
uvx chroma-mcp-server設定
{
"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"
}
}
}
}