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Q-CLI MCP Memory Server

@gengisb

Repository

About Q-CLI MCP Memory Server

an MCP server implementing a memory feature for Q CLI

Basic information

Category

Memory & Knowledge

Runtime

python

Transports

stdio

Publisher

gengisb

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "QCLI-memories-mcp": {
      "command": "python3",
      "args": [
        "mcp_memory_server.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Q-CLI MCP Memory Server?

It is a contextual memory system designed for CLI tools used by developers and cloud engineers. It persists memory across sessions, helping AI assistants remember user information, preferences, code patterns, and architecture decisions.

How to use Q-CLI MCP Memory Server?

Clone the repository, install dependencies with pip install -r requirements.txt, and run python3 mcp_memory_server.py. Then configure your MCP client by adding an entry to mcp.json with command python and args pointing to the path of memories_server.py.

Key features of Q-CLI MCP Memory Server

  • Intelligent memory storage with tags (#code, #architecture, #personal, #project)
  • Contextual retrieval via exact key, keyword search, or context inference
  • Multi‑user support with separate memory spaces per user
  • Progressive learning that builds understanding over time

Use cases of Q-CLI MCP Memory Server

  • Remembering personal preferences and programming language choices
  • Storing AWS infrastructure patterns and configurations
  • Recording previous errors and their solutions
  • Tracking project‑specific requirements and deadlines
  • Eliminating the need to repeat technical context in each session

FAQ from Q-CLI MCP Memory Server

Does Q-CLI MCP Memory Server support cloud‑based memory?

Currently it supports only a local SQLite database. Cloud‑based memory is a planned future goal.

How does Q-CLI MCP Memory Server categorize memories?

It automatically assigns tags such as #code, #architecture, #personal, and #project to categorize stored information.

How does Q-CLI MCP Memory Server handle multiple users?

It identifies users from conversation context and maintains separate memory spaces for each user, with potential for shared project contexts across users.

What are the installation requirements for Q-CLI MCP Memory Server?

Python is required. The server is installed by cloning the repository and running pip install -r requirements.txt.

How do I configure Q-CLI MCP Memory Server in my MCP client?

Add an entry to your mcp.json file with "command": "python" and "args": ["PATH_TO_YOUR_FILE/memories_server.py"], replacing the path with the actual location of the file.

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