Skip to main content

Conversation memory and session management MCP server for Amazon Q CLI with ChromaDB real-time sync

Project description

AWS Q CLI Memory MCP Server

A Model Context Protocol (MCP) server that provides conversation memory and session management for Amazon Q CLI.

🎯 Key Features

  • Automatic Conversation Saving: Real-time sync of Q CLI conversations to ChromaDB
  • Session Management: Organize conversations by topics/sessions
  • Context Restoration: Resume previous conversations with full context memory
  • Semantic Search: Search through conversation history using natural language

🚀 Quick Start (PyPI Installation)

1. MCP Configuration

Add to ~/.config/amazon-q/mcp_config.json:

{
  "mcpServers": {
    "q-mem-mcp-server": {
      "command": "uvx",
      "args": ["q-mem-mcp-server@latest"],
      "env": {
        "Q_CLI_DB_PATH": "~/Library/Application Support/amazon-q/data.sqlite3",
        "Q_MEM_VERBOSE": "true"
      },
      "disabled": false,
      "autoApprove": [
        "start_session",
        "resume_session", 
        "search_memory_by_session_id",
        "get_storage_stats",
        "list_sessions"
      ]
    }
  }
}

2. Usage

# Start Q CLI
q chat

# Start a new session
start_session(description="backendDev")
or 
session start "backendDev" 
# Chat normally (automatically saved)
# ... have conversations ...

# List sessions
list_sessions()

# Resume session (loads full context)
resume_session(session_id="backendDev")

🛠️ Available Commands

Command Description
start_session(description) Start a new session
list_sessions() List all sessions
resume_session(session_id) Resume session with full context
search_memory_by_session_id(session_id, query) Search previous conversations
delete_session(session_id, confirm=true) Delete a session
get_storage_stats() Check storage status

🔧 Technology Stack

  • ChromaDB: Vector database for conversation storage and search
  • SQLite WAL: Real-time sync with Q CLI database
  • Sentence Transformers: Semantic search embeddings
  • MCP Protocol: Communication with Amazon Q

📁 Data Storage

  • ChromaDB: ~/.Q_mem/chroma_db/
  • Sync State: ~/.Q_mem/sync_state.json
  • Logs: ~/.Q_mem/q_mem.log

🔄 Auto-Sync Features

Q CLI conversations are automatically saved to ChromaDB in real-time:

  • Real-time Detection: Checks for new conversations every 2 seconds
  • Partial Failure Handling: Saves successful conversations even if some fail
  • Auto Recovery: Automatically recovers from consecutive failures
  • State Restoration: Restores sync state after restart

💡 Usage Tips

  1. Session Organization: Separate conversations by topics
  2. Semantic Search: Use natural language rather than exact keywords
  3. Context Utilization: Use resume_session for complete conversation restoration
  4. Regular Cleanup: Delete unnecessary sessions with delete_session

Memory Issues

# Clean up old sessions
cleanup_old_sessions(days=30, confirm=true)

📦 Installation Methods

PyPI

{
  "mcpServers": {
    "q-mem-mcp-server": {
      "command": "uvx",
      "args": ["q-mem-mcp-server@latest"],
      "env": {
        "Q_CLI_DB_PATH": "~/Library/Application Support/amazon-q/data.sqlite3",
        "Q_MEM_VERBOSE": "true"
      }
    }
  }
}

📄 License

MIT License

🔗 Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

q_mem_mcp_server-1.0.1.tar.gz (24.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

q_mem_mcp_server-1.0.1-py3-none-any.whl (26.3 kB view details)

Uploaded Python 3

File details

Details for the file q_mem_mcp_server-1.0.1.tar.gz.

File metadata

  • Download URL: q_mem_mcp_server-1.0.1.tar.gz
  • Upload date:
  • Size: 24.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for q_mem_mcp_server-1.0.1.tar.gz
Algorithm Hash digest
SHA256 19487e21e210ef4105ad44c13bbbf6933b5873164c2d5598657f84915b5f6817
MD5 c275d773aab2345c2a8698e5b1e4a153
BLAKE2b-256 39304767719c1a5c6edbb14576551e259aeadd25a872a5dcda4461516f161f41

See more details on using hashes here.

File details

Details for the file q_mem_mcp_server-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for q_mem_mcp_server-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 e156c0867017b3a444d8958d26d3f4f1ffeef6613e735c25599e6a44e2735ce1
MD5 593b223865597985b8be10917a996ff2
BLAKE2b-256 4a5161c9942294d24ee6dd30e851634c2154e3135148f123a16101e485654fc5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page