AI & MemoryMCP RegistrypypiB · 70

Memory Kernel MCP server

Name: Memory Kernel
Author: Artem362

io.github.Artem362 · Updated 4mo ago

Local-first memory for AI agents: SQLite FTS5, deterministic recall, no vector DB, no cloud.

At a glance

Memory Kernel is an MCP server in the AI & Memory category. It runs locally over stdio via `uvx amormorri-memory-kernel`, and declares no required credentials. It scores B (70/100) on the MCP Skills Hub health score as of Oct 28, 2026.

Source 3

One-click install

VS Code VS Code Insiders Cursor

Opens your editor and pre-fills the config. Your editor will ask before adding it.

How to install Memory Kernel in your AI client

Setup for Claude Code, Claude Desktop, Cursor, Codex, Windsurf, Cline and VS Code — copy-paste ready.

How to install Memory Kernel in Claude CodeAnthropic's agentic CLI

Add the server

bash

claude mcp add memory-kernel -- uvx amormorri-memory-kernel

2
Verify it's connected
bash
```
claude mcp list
```
Sharing it with your team?
Add `--scope project` to write it to .mcp.json in the repository root, which you can commit (with the secrets left as environment variables).
Use it in a session
Ask Claude to use the tools this server exposes. It discovers them automatically.

How to install Memory Kernel in Claude DesktopDesktop app (MCP config)

Open your MCP config
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

Add this server

json

{
  "mcpServers": {
    "memory-kernel": {
      "command": "uvx",
      "args": [
        "amormorri-memory-kernel"
      ]
    }
  }
}

Restart Claude Desktop
The tools appear under the 🔌 menu once the app reloads.

How to install Memory Kernel in CursorAI-first code editor

Create / edit .cursor/mcp.json in your project

json

{
  "mcpServers": {
    "memory-kernel": {
      "command": "uvx",
      "args": [
        "amormorri-memory-kernel"
      ]
    }
  }
}

Enable it
Cursor Settings → MCP → toggle the server on. Tools become available to the Composer/Agent.

How to install Memory Kernel in Codex CLIOpenAI coding agent

Add to ~/.codex/config.toml

toml

[mcp_servers.memory-kernel]
command = "uvx"
args = ["amormorri-memory-kernel"]

Run Codex
Codex loads MCP servers from config.toml on startup and exposes their tools to the agent.

How to install Memory Kernel in WindsurfCodeium's agentic IDE

Edit ~/.codeium/windsurf/mcp_config.json

json

{
  "mcpServers": {
    "memory-kernel": {
      "command": "uvx",
      "args": [
        "amormorri-memory-kernel"
      ]
    }
  }
}

Reload
Windsurf → Cascade → refresh MCP servers. Cascade can now call the tools.

How to install Memory Kernel in ClineVS Code autonomous agent

Open Cline → MCP Servers → Configure
Adds to cline_mcp_settings.json.

Add the server

json

{
  "mcpServers": {
    "memory-kernel": {
      "command": "uvx",
      "args": [
        "amormorri-memory-kernel"
      ]
    }
  }
}

How to install Memory Kernel in VS CodeCopilot / MCP support

Create .vscode/mcp.json

json

{
  "servers": {
    "memory-kernel": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "amormorri-memory-kernel"
      ]
    }
  }
}

Start it
VS Code shows a ▶ Start action above the server entry. Agent mode (Copilot Chat) can then use the tools.

What does Memory Kernel need from you?

Configuration only — Declares config values but no credentials.

MEMORY_KERNEL_DBoptionalEnvironment variable
Path to the SQLite database file (defaults to .memory-kernel/memory.db in the working directory)

Pass secrets through your shell environment rather than committing them into a config file.

What tools does Memory Kernel expose?

This server runs as a local package. We only query remote servers for their tool list — asking this one would mean executing it, so its tools are listed in the documentation below.

What the code can do

Source analysis currently covers npm packages only. This server ships as a Python package, which needs a different parser.

Before you install

Signals gathered from the source repo and package registry — not a safety verdict.

What it can reach

Runs code on your machine — Executes as a local process with your user's permissions, including filesystem access.
Downloads at launch — The package is fetched from its registry each run unless you pin a version.

Last commit 4 months ago — Actively maintained.
3 GitHub stars — Very little community usage so far.

Client compatibility

Claude Code: NativeClaude Desktop: NativeCursor: NativeCodex CLI: NativeWindsurf: NativeCline: NativeVS Code: Native

Health score

B · 70

Maintenance, adoption, transparency and packaging — not a safety audit. How this is calculated

Maintenance30%85%
Last commit 135 days ago.
Adoption20%18%
3 stars.
Transparency20%75%
3/4: ✓ public source repo, ✓ declared license, ✓ documentation, ✗ discoverable tool list.
Provenance15%75%
Links to its own repository; package linkage unverified.
Packaging15%100%
Publishes a pinned version (0.3.2).

Documentation

Full README

Memory Kernel

Memory Kernel is a small local memory layer for AI agents.

It helps you save useful things such as decisions, constraints, tasks, facts, and notes in a local SQLite database, then pull back only the few memories that matter for the current task.

Published package name on PyPI: amormorri-memory-kernel CLI command after install: memory-kernel

Practical guide in Ukrainian: docs/OPERATING_GUIDE_UK.md

Release notes: CHANGELOG.md

Contents

What It Does
Start In 5 Minutes
Typical Workflow
Which Command To Use
Write: `remember`, `ingest`
Read: `search`, `context`, `wake-up`, `stats`
Inspect / edit: `list`, `show`, `update`, `delete`
Lifecycle: `forget` / `restore`, `revise`, `decay`
Maintain: `completion`, `verify`
Backup: `export`, `import`
Use With An LLM (MCP)
How It Works
Data Flow
Component Diagram
Memory Record Schema
Ukrainian Inflection Bridging
Why It Stays Lightweight
Who It Is For
Project Status
Native Accelerator
Feedback

What It Does

In plain English, Memory Kernel does 4 things:

Stores memory locally on your machine.
Keeps memory structured enough to stay useful.
Finds relevant records without a heavy vector stack.
Builds a small context pack instead of dumping everything into the prompt.

This project is not trying to create a magical black-box memory. It is trying to create a memory layer you can inspect, control, export, and trust.

Start In 5 Minutes

If you just want to try it, do this:

Excerpt — the full document is on GitHub.

Alternatives to Memory Kernel

Maintain Memory Kernel? Add a badge to your README

Shows its health grade, and links readers to install steps for every client.

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Catalog data refreshed Oct 28, 2026. Something wrong? Report it.