Memory Storage
STDIOPython-based memory plugin using SQLite for persistent storage.
Python-based memory plugin using SQLite for persistent storage.
A Python-based memory plugin that uses SQLite for persistent storage.
This plugin provides memory storage functionality using SQLite as the backend database. It's designed to store and manage data persistently across sessions.
Environment Configuration
Create a .env
file in the root directory with the following configuration:
MEMORY_DB_PATH=/path/to/your/memory.sqlite
You can use the provided .env.example
as a template:
cp .env.example .env
Dependencies
The project requires Python and uses SQLite for data storage. Make sure you have Python installed on your system.
rename .env.example to .env and edit the values to your needs:
Locate claude_desktop_config.json and use the template below to add "MQTT Bridge" to the mcpServers section. MacOs: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: C:\Users<username>\AppData\Roaming\Claude\claude_desktop_config.json
{ "mcpServers": { "memory_recall": { "command": "/path/to/python3", "args": [ "/path/2/your/cloned/repository/memory_plugin.py" ] } } }
The SQLite database path is configured through the MEMORY_DB_PATH
environment variable. This should point to where you want the SQLite database file to be stored.
Current configuration:
MEMORY_DB_PATH=/path/to/your/dabatase.sqlite
Refer to the @mcp.resource and @mcp.tool decorated functions in the memory_plugin.py file
Examples to type in the chat:
memory://load
to load the saved memories at new chat startSave into the memory, under aNewName category, the following: a new message with important info to remember
Save the relevant points of the conversation into the memory under aNewName category
When contributing to this project:
.env
file private.env.example
for sharing template configurationsThis project is licensed under the MIT License.