A Mem MCP

Name: A Mem MCP
Author: DiaaAj

by DiaaAjversion 0.2.1i★ –iRuns on your computer

Registry nameio.github.DiaaAj/a-mem-mcp

Install

Overview

Description from the maker (original English)

Self-evolving memory system for AI agents

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 checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 112/wk · ★ –

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
You need to fill in: OPENAI_API_KEY

Install

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

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: LLM_BACKEND, LLM_MODEL, OPENAI_API_KEY, EMBEDDING_MODEL, CHROMA_DB_PATH

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

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": {
    "a-mem": {
      "command": "uvx",
      "args": [
        "a-mem"
      ],
      "env": {
        "LLM_BACKEND": "your-value",
        "LLM_MODEL": "your-value",
        "OPENAI_API_KEY": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "CHROMA_DB_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add a-mem --env LLM_BACKEND=your-value --env LLM_MODEL=your-value --env OPENAI_API_KEY=your-value --env EMBEDDING_MODEL=your-value --env CHROMA_DB_PATH=your-value -- uvx a-mem

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": {
    "a-mem": {
      "command": "uvx",
      "args": [
        "a-mem"
      ],
      "env": {
        "LLM_BACKEND": "your-value",
        "LLM_MODEL": "your-value",
        "OPENAI_API_KEY": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "CHROMA_DB_PATH": "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": {
    "a-mem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "a-mem"
      ],
      "env": {
        "LLM_BACKEND": "your-value",
        "LLM_MODEL": "your-value",
        "OPENAI_API_KEY": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "CHROMA_DB_PATH": "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

LLM_BACKEND env
LLM backend to use (openai, ollama, sglang, or openrouter)
LLM_MODEL env
LLM model name (e.g., gpt-4o-mini, llama2, etc.)
OPENAI_API_KEY secret required env
OpenAI API key (required if LLM_BACKEND=openai)
EMBEDDING_MODEL env
Sentence transformer model for embeddings
CHROMA_DB_PATH env
ChromaDB storage directory path

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

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 9, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account DiaaAj, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… 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 0% of the other 5747 servers in this category
Published to the registry more recently than 2% of the other 5747 servers in this category
Basic checks equal to or better than 100% of the other 5747 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 A Mem MCP safe?

It passed 1 of 1 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?

You need to fill in: OPENAI_API_KEY

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 –, and the latest version (0.2.1) reached the registry 10 months ago.

Which apps can use it?

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

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

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

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↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Install

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Install

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsWidely used★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

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.

A-MEM: Self-evolving memory for coding agents

mcp-name: io.github.DiaaAj/a-mem-mcp

A-MEM is a self-evolving memory system for coding agents. Unlike simple vector stores, A-MEM automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships. Memories don't just get stored—they evolve and connect over time.

Currently tested with Claude Code. Support for other MCP-compatible agents is planned.

Quick Start

Install

pip install a-mem

Add to Claude Code

claude mcp add a-mem -s user -- a-mem-mcp \

-e LLM_BACKEND=openai \ -e LLM_MODEL=gpt-4o-mini \ -e OPENAI_API_KEY=sk-...

That's it! A session-start hook installs automatically to remind Claude to use memory.

Note: Memory is stored per-project in ./chroma_db. For global memory across all projects, see Memory Scope.

Uninstall

a-mem-uninstall-hook   # Remove hooks first

pip uninstall a-mem

How It Works

t=0              t=1                t=2

◉───◉ ◉───◉ ◉ │ ╱ │ ╲ ◉ ◉──┼──◉ │ ◉

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━▶ self-evolving memory

Add a memory → A-MEM extracts keywords, context, and tags via LLM
Find neighbors → Searches for semantically similar existing memories
Evolve → Decides whether to link, strengthen connections, or update related memories
Store → Persists to ChromaDB with full metadata and relationships

The result: a knowledge graph that grows smarter over time, not just bigger.

Features

Self-Evolving Memory Memories aren't static. When you add new knowledge, A-MEM automatically finds related memories and strengthens connections, updates context, and evolves tags.

Semantic + Structural Search Combines vector similarity with graph traversal. Find memories by meaning, then explore their connections.

Peek and Drill Start with breadth-first search to capture relevant memories via lightweight metadata (id, context, keywords, tags). Then drill depth-first into specific memories with read_memory_note for full content. This minimizes token usage while maximizing recall.

MCP Tools

A-MEM exposes 8 tools to your coding agent:

Tool	Description
`add_memory_note`	Store new knowledge (async, returns immediately)
`search_memories`	Semantic search across all memories
`search_memories_agentic`	Search + follow graph connections
`search_memories_by_time`	Search within a time range
`read_memory_note`	Get full details (supports bulk reads)
`update_memory_note`	Modify existing memory
`delete_memory_note`	Remove a memory
`check_task_status`	Check async task completion

Example Usage

# The agent calls these automatically, but here's what happens:

Store a memory (returns task_id immediately)

add_memory_note(content="Auth uses JWT in httpOnly cookies, validated by AuthMiddleware")

Search later

search_memories(query="authentication flow", k=5)

Deep search with connections

search_memories_agentic(query="security", k=5)

Advanced Configuration

JSON Config

For more control, edit ~/.claude/settings.json (global) or .claude/settings.local.json (project):

"mcpServers": { "a-mem": { "command": "a-mem-mcp", "env": { "LLM_BACKEND": "openai", "LLM_MODEL": "gpt-4o-mini", "OPENAI_API_KEY": "sk-..." } } } }

Environment Variables

Variable	Description	Default
`LLM_BACKEND`	`openai`, `ollama`, `sglang`, `openrouter`	`openai`
`LLM_MODEL`	Model name	`gpt-4o-mini`
`OPENAI_API_KEY`	OpenAI API key	—
`EMBEDDING_MODEL`	Sentence transformer model	`all-MiniLM-L6-v2`
`CHROMA_DB_PATH`	Storage directory	`./chroma_db`
`EVO_THRESHOLD`	Evolution trigger threshold	`100`

Memory Scope

Project-specific (default): Each project gets isolated memory in ./chroma_db
Global: Share across projects by setting CHROMA_DB_PATH=~/.local/share/a-mem/chroma_db

Alternative Backends

Ollama (local, free)

claude mcp add a-mem -s user -- a-mem-mcp \

-e LLM_BACKEND=ollama \ -e LLM_MODEL=llama2

OpenRouter (100+ models)

claude mcp add a-mem -s user -- a-mem-mcp \

-e LLM_BACKEND=openrouter \ -e LLM_MODEL=anthropic/claude-3.5-sonnet \ -e OPENROUTER_API_KEY=sk-or-...

Hook Management (Claude Code)

The session-start hook reminds Claude to use memory tools. It installs automatically with Claude Code, but you can manage it manually:

a-mem-install-hook     # Install/reinstall hook

a-mem-uninstall-hook # Remove hook completely

Python API

Use A-MEM directly in Python (works with any agent or application):

from agentic_memory.memory_system import AgenticMemorySystem

memory = AgenticMemorySystem( llm_backend="openai", llm_model="gpt-4o-mini" )

Add (auto-generates keywords, tags, context)

memory_id = memory.add_note("FastAPI app uses dependency injection for DB sessions")

Search

results = memory.search("database patterns", k=5)

Read full details

note = memory.read(memory_id) print(note.keywords, note.tags, note.links)

Research

A-MEM implements concepts from the paper:

A-MEM: Agentic Memory for LLM Agents

Xu et al., 2025

arXiv:2502.12110

A Mem MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

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

Context7

Codebase Memory

Exa

README from the maker

A-MEM: Self-evolving memory for coding agents

Quick Start

Install

Add to Claude Code

Uninstall

How It Works

Features

MCP Tools

Example Usage

Store a memory (returns task_id immediately)

Search later

Deep search with connections

Advanced Configuration

JSON Config

Environment Variables

Memory Scope

Alternative Backends

Hook Management (Claude Code)

Python API

Add (auto-generates keywords, tags, context)

Search

Read full details

Research