AI Memory

Name: AI Memory
Author: alphaonedev

by alphaonedevversion 0.5.1i★ 56iRuns on your computer

Registry nameio.github.alphaonedev/ai-memory

Install

Overview

Description from the maker (original English)

Persistent memory for any AI — zero token cost until recall

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi2 of 2 passedChecked from public information; code not scanned yet
UsageiEarly★ 56

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 2 of 2 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: AI_MEMORY_DB

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ai-memory": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "AI_MEMORY_DB",
        "ghcr.io/alphaonedev/ai-memory:0.5.1",
        "mcp",
        "--tier",
        "semantic"
      ],
      "env": {
        "AI_MEMORY_DB": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ai-memory --env AI_MEMORY_DB=your-value -- docker run -i --rm -e AI_MEMORY_DB ghcr.io/alphaonedev/ai-memory:0.5.1 mcp --tier semantic

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ai-memory": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "AI_MEMORY_DB",
        "ghcr.io/alphaonedev/ai-memory:0.5.1",
        "mcp",
        "--tier",
        "semantic"
      ],
      "env": {
        "AI_MEMORY_DB": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ai-memory": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "AI_MEMORY_DB",
        "ghcr.io/alphaonedev/ai-memory:0.5.1",
        "mcp",
        "--tier",
        "semantic"
      ],
      "env": {
        "AI_MEMORY_DB": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

AI_MEMORY_DB env
Path to the SQLite database file

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

All apps, with pros and cons →

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 10, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account alphaonedev, which owns the repo
✓ Pass
Still maintained
Code last changed today
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 97% of the other 5861 servers in this category
Published to the registry more recently than 9% of the other 5861 servers in this category
Basic checks equal to or better than 100% of the other 5861 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is AI Memory safe?

It passed 2 of 2 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed today, and the latest version (0.5.1) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Ruflo, Context7, Metabase

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Ruflo

Agent teams, swarms, memory and hooks for Claude Code and Codex, served over MCP.

by ruvnetWidely used↓ 74.3K/wk★ 81.4KUpdated today

Runs on your computer

Install

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 1.2M/wk★ 64.4KUpdated yesterday

Computer or cloud

Install

Metabase

Lets AI clients search, explore, query, and visualize data in a Metabase instance.

by metabaseWidely used★ 50.3KUpdated 6 months ago

Runs in the cloud

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

ai-memory universal AI memory

ai-memory is a persistent memory system for AI assistants. It works with any AI that supports MCP -- Claude, ChatGPT, Grok, Llama, and more. It stores what your AI learns in a local SQLite database, ranks memories by relevance when recalling, and auto-promotes important knowledge to permanent storage. Install it once, and every AI assistant you use remembers your architecture, your preferences, your corrections -- forever.

Choose your installation path

You are…	Your deployment is…	Start here
A single developer trying ai-memory	One AI client on a laptop	`docs/install-quickstart.md` — 5-min super-simple install + LLM-backend wired in one block
An engineer / architect	Single-node production, or multiple agents on one node	`docs/INSTALL.md` → `docs/production-deployment.md`
An engineer / architect	Multi-server / multi-rack / multi-DC / swarm / hive / federation	`docs/enterprise-deployment.md` — 8 topologies, singleton → multi-region
An engineer / architect	PostgreSQL + Apache AGE storage (multi-writer, 10M+ memories, KG-heavy)	`docs/postgres-age-guide.md` — first-class postgres operator guide
A decision-maker evaluating adoption	—	`docs/audience/decision-maker.html`

Configuring the LLM backend (xAI Grok, OpenAI, Anthropic, Gemini, DeepSeek, Kimi, Qwen, Mistral, Groq, Together, Cerebras, OpenRouter, Fireworks, LMStudio, vLLM, llama.cpp server, or local Ollama)? See docs/integrations/llm-backends.md — the MCP env-block recipe is the same regardless of installation path.

v0.9.0 — current release. A security-hardening and code-review release: 49 fixes from a 5-lane adversarial review (#1885–#1935) plus a smaller set of additive features. The headline change is a secure-default flip: agent attestation is required by default on HTTP direct-write (#1751, surface-scoped by #1985) — an unsigned HTTP POST /api/v1/memories (+/bulk) is rejected (403 ATTESTATION_FAILED) instead of landing attest_level="claimed", unless the operator sets the explicit opt-out AI_MEMORY_REQUIRE_AGENT_ATTESTATION=0. The MCP memory_store and CLI store surfaces are the operator-as-actor path and stay permissive by default (an unsigned write lands claimed); =1 forces strict on every surface. (The v0.9.0 GA shipped this as require-*everywhere*, which was unsatisfiable on MCP hosts — corrected to surface-scoped in the current release.) Alongside it, the mandatory-hook-presence enforcement gate now fires on both the MCP write path (#1885) and the HTTP write path (#1924), closing a silent-bypass gap where a configured mandatory hook could be skipped on one surface but not the other. The hardening pass also closes bulk_create per-row attestation gating (#1919), routes inbound federated PENDING approvals through the registered-approver gate (#1920), tightens team/unit/org visibility scope so it is no longer over-broad across the namespace hierarchy (#1921), and confines skill_register's folder_path import under the configured root with a symlink jail (#1923). A new non-argv credential channel — AI_MEMORY_STORE_URL / AI_MEMORY_STORE_URL_FILE (a 0600 file) — keeps the postgres/store password off world-readable /proc/ /cmdline and ps (#1927). Additive feature work: agent-authored skill memories with a parameters_schema + invocation_record (B7-SKILL, #1865), the recall_observations shadow-feedback loop (#1706), a memory-derivation lineage DAG (memory_lineage, #1859), and an opt-in vector-search minimal slice (#1005). Surface: schema v78, 101 MCP tools at --profile full (100 callable + the always-on memory_capabilities bootstrap) / 7 at --profile core, 92 HTTP route registrations (78 unique URL paths), 89 CLI subcommands under --features sal/sal-postgres (87 in the default build), 9 typed MemoryLink relations, a 28-field Memory. Runs on two production backends behind one identical API — embedded SQLite and PostgreSQL + Apache AGE — across desktop, server, and on-device (iOS + Android). Everything is additive over v0.8.1 except the attestation and hook-enforcement flips, which are secure-by-default breaking changes — review them before upgrading. Full changelog: CHANGELOG.md §"[0.9.0] — 2026-07-08".

v0.8.0 (`distributed-coordination`) — prior release. This is the release where the memory substrate becomes a coordination substrate. It adds the distributed-coordination machinery from #1709: a typed action DAG with a real state machine (memory_action_*), TTL-bounded single-holder leases (memory_lease_*), Ed25519-signed signals (memory_signal_*), Ed25519-attested checkpoints (memory_checkpoint_*), and frozen, replayable routines (memory_routine_*) — so a heterogeneous fleet of agents can take turns, hand off work, and prove who said what without having to trust each other. It layers typed cognition on top (the Goal/Plan/Step memory kinds, a lifecycle_state machine, and the decomposes_into / depends_on / advances link relations), hardens federation secure-by-default (peer enrollment ON by default #1789, per-transition signatures #1718, per-write content attestation #1464, transition-replay nonces #1805, outbound peer-cert pinning #1678), and ships governance that actually blocks — the Claude Code PreToolUse hook is reworked to a type:command wrapper so a substrate Refuse truly denies the tool (#1811). At the v0.8.0 release, surface was: schema v70, 100 MCP tools at --profile full (99 callable + the always-on memory_capabilities bootstrap) / 7 at --profile core, 91 HTTP route registrations (78 unique URL paths), 83/85 CLI subcommands, 9 typed MemoryLink relations, a 27-field Memory. Runs on two production backends behind one identical API — embedded SQLite and PostgreSQL + Apache AGE — across desktop, server, and on-device (iOS + Android). Everything is additive over v0.7.0; review the secure-default flips before upgrading. Full release notes: docs/v0.8.0/release-notes.md.

v0.7.0 (`attested-cortex`) — prior release. Rolled together the cortex-fluent legibility work with the full v0.7 trust + A2A scope from ROADMAP §7.3, plus (per operator directive 2026-05-09) the originally-v0.7.1 postgres+AGE first-class work, plus the post-grand-slam ship-readiness wave (Batman Forms 1-6 + 7th-form Option-B foundation + QW-1/2/3 + reconciliation security sweep). The substrate becomes both more articulate (capabilities v3, named loader tools, compacted schemas, Batman MemoryKind vocabulary, persona/atomisation/multistep-ingest primitives) and cryptographically trustworthy (Ed25519 attestation, sidechain transcripts, programmable 25-event hook pipeline, enforced namespace inheritance, V-4 cross-row signed-events hash chain). v0.7.0 also ships postgres + Apache AGE as a first-class storage backend — ai-memory serve --store-url postgres://… for live daemon use, schema parity across both backends (at the v0.7.0 release, sqlite + postgres converged on logical schema v57, where CURRENT_SCHEMA_VERSION was 57; the v0.8.0 release substrate has advanced this lockstep to schema 70, with the additive v58–v70 coordination + visibility tables landed on both backends — see CLAUDE.md §Database for the v58–v70 ladder) (canonical anchors: src/storage/migrations.rs for sqlite + src/store/postgres.rs for postgres); on-disk migration files end at migrations/sqlite/0047_v56_list_composite_indexes.sql and the postgres in-process migrate_v57() ladder arm (file-name counters lag the logical schema version because both ladders apply post-v34

Only the beginning is shown; read the rest in the repo

AI Memory

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

Which apps can use it

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Ruflo

Context7

Metabase

README from the maker

Choose your installation path