MAGNEMO

Name: MAGNEMO
Author: magnemo-ai

by magnemo-aiversion 0.6.11i★ –iRuns on your computer

Registry nameai.magnemo/magnemo

Install

Overview

Description from the maker (original English)

Persistent Memory for AI Agents, in plain local files. No network calls of its own.

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
UsageiNot measured yet★ –

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: MAGNEMO_VAULT

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: MAGNEMO_VAULT, MAGNEMO_AGENT

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": {
    "magnemo": {
      "command": "uvx",
      "args": [
        "magnemo-mcp"
      ],
      "env": {
        "MAGNEMO_VAULT": "your-value",
        "MAGNEMO_AGENT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add magnemo --env MAGNEMO_VAULT=your-value --env MAGNEMO_AGENT=your-value -- uvx magnemo-mcp

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": {
    "magnemo": {
      "command": "uvx",
      "args": [
        "magnemo-mcp"
      ],
      "env": {
        "MAGNEMO_VAULT": "your-value",
        "MAGNEMO_AGENT": "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": {
    "magnemo": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "magnemo-mcp"
      ],
      "env": {
        "MAGNEMO_VAULT": "your-value",
        "MAGNEMO_AGENT": "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

MAGNEMO_VAULT required env
Absolute path to the vault folder (create one with: magnemo init ./vault). Plain markdown files you own.
MAGNEMO_AGENT env
The name this agent signs its entries with. Default: agent.

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain magnemo.ai (the registry checks domain ownership)
… 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 7234 servers in this category
Published to the registry more recently than 81% of the other 7234 servers in this category
Basic checks equal to or better than 100% of the other 7234 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 MAGNEMO 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: MAGNEMO_VAULT

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 (0.6.11) reached the registry 8 days 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:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

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

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated 44 days ago

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.

The Memory MCP. Your AI remembers. You keep what matters.

MAGNEMO is Memory for your AI, kept on your computer in plain files. Your AI writes down what it learns as it works; nothing becomes Memory until you approve it, and every Memory shows who wrote it and who approved it.

Your agent writes one line down and keeps working. Say keep, and it is Memory.

Site · Manual · Changelog · X @Magnemo_AI · Known limits

Install in one paste

In three lines:

pip install MAGNEMO      # Python 3.11 or newer

magnemo init # makes the vault: a folder of plain files magnemo mount # writes .mcp.json, the file Claude Code reads, and the first line in CLAUDE.md

Or let your agent do it. Open Claude Code in any of your project folders, and paste this. (Its magnemo mount step writes .mcp.json, the file Claude Code reads, and a short block in CLAUDE.md that tells every new session where this project's Memory is. In Cursor, Windsurf or another client, use the block for your client under "Install in your client".)

Set up MAGNEMO in this project:

Install it: pip install MAGNEMO. It needs Python 3.11 or newer. If pip can't find it, install uv (curl -LsSf https://astral.sh/uv/install.sh | sh) and then run: uv tool install MAGNEMO
Initialize the vault: magnemo init
Register the MCP server: run magnemo mount — it adds MAGNEMO to this project's MCP config and keeps any servers already there.
Verify: run magnemo doctor and confirm everything passes.
Then ask me to restart you, so MAGNEMO's tools load, and to say this when you are back: "Look around this folder, tell me what this project is for, and stage that as the first note." Your agent never waits on you. When you want something kept, say keep.

If anything fails, show me what went wrong and fix it if you can.

Plant the seed: one paste, and your agent grows a Memory.

After the restart, say it: Look around this folder, tell me what this project is for, and stage that as the first note. Your agent writes one line down and keeps working. Say keep, and it is Memory. Then ask what it remembers.

Works with

One server, the same in every client. Tested where it says so; the rest follow each client's own docs.

Client	Tested	How
Claude Code	yes: Oct 26–28, 2026, Claude Code 2.1.309. Seven tools; the yes in the chat; `pending` reads a body.	`magnemo mount`, or `claude mcp add magnemo -e MAGNEMO_VAULT=/absolute/path/to/vault -- uvx magnemo-mcp`
Claude Desktop	untested end to end	the `uvx` block under "Install in your client", with absolute paths
Cursor	untested	the Add to Cursor link below, or `.cursor/mcp.json`
VS Code	untested	`.vscode/mcp.json`
Windsurf	untested	`~/.codeium/windsurf/mcp_config.json`
Cline	untested	`cline_mcp_settings.json`
Continue	untested	`~/.continue/config.yaml`
Gemini CLI	untested	`~/.gemini/settings.json`
Codex CLI	untested	`~/.codex/config.toml`
Zed	untested	`settings.json` → `context_servers`

Each client's exact block is under "Install in your client".

How it compares

Five questions, answered from each project's own docs (read Oct 12, 2026, checked again Oct 22; the pages are linked under the table).

	MAGNEMO	Mem0	Zep	Letta	Basic Memory
Where the memory lives	Plain markdown files in a folder on your computer	A hosted platform run by Mem0; open source: a local Qdrant store and a SQLite history file	Zep: a managed cloud service, or in your own VPC. Graphiti, its open-source engine: a graph database you run	Markdown files in a git repository that belongs to the agent: hosted by Letta, or on your device in local mode	Markdown files on your disk with a local SQLite index; an optional cloud
Who approves a write	You. An agent's write waits in staging until your yes	An LLM extracts facts from the messages and stores them; their docs describe no approval step	Messages are ingested into the graph as they arrive; their docs describe no approval step	The agent updates its own memory; the background review "does not ask you for approval"	The assistant writes notes directly; the cloud has suggested edits that can be accepted or rejected
Author and approver on every entry	Both, in each file's header (`author`, `reviewed_by`) and in an append-only ledger	User, agent, app and run ids, timestamps, and a change history per memory; their docs name no approver field	When a fact was true and when it stopped, traced to its source episode; their docs name no approver field	Every memory edit is a git commit; their docs do not say what the commit records	Title, type, tags and dates; `author` is a field you may add; their docs name no approver field
Network calls of its own	None. No model call and no embedding call; `git push` to a backup, if you add one	OpenAI by default for the model and the embeddings; other providers are listed, Ollama among them	Zep is a cloud API. Graphiti defaults to OpenAI; local model servers are documented	Local mode keeps state on your device; inference goes to the provider you choose, which can be a local one	Runs locally; the default embeddings run on your machine with no API key
What you can take back	A no is kept with its reason; a replaced note is archived with a forward link; nothing deletes; the files are yours to edit	Delete, update, and a history per memory; export is on the hosted platform	Delete nodes, edges and episodes; a replaced fact is invalidated, not deleted	The git history of every memory edit; the files can be read and edited	Plain files you edit and can track with git; a delete tool; the cloud keeps every saved version

Where each of them is ahead. Mem0 extracts memories for you, searches them by meaning, and has Python and JavaScript SDKs, a REST API and a hosted platform. Zep keeps a knowledge graph that knows when each fact was true, as a managed service with SDKs in three languages. Letta is a whole agent platform, with an SDK, a CLI and background agents that tend the memory. Basic Memory searches by keyword and by meaning with embeddings that run on your machine, links notes into a graph, and syncs through its cloud. MAGNEMO has none of that: its search is keyword search (KNOWN_LIMITS.md), there is no graph and no hosted service. What it has is the approval and the record.

Their pages: Mem0 overview, platform and open source, add, history, quickstart, delete, export · Zep concepts, facts, security, deleting data, Graphiti · Letta MemFS, memory settings, local mode · Basic Memory README, what it is, tools, note format, semantic search, suggestions, file history. A cell that is wrong or out of date: open an issue and it is fixed.

Listed on the official MCP registry (ai.magnemo/magnemo) · PyPI · mcpservers.org · Glama · awesome-mcp-servers. Tested on every push, on Python 3.9, 3.11 and 3.12: 370 tests, as of Oct 28, 2026 (the runs).

What's new

0.6.11 · Oct 28, 2026 · magnemo mount writes the first line in CLAUDE.md, so every new session knows where this project's Memory is. pending reads a note nobody has kept yet.
0.6.10 · Oct 26, 2026 · Your agent never stops to ask. Say keep in the chat, and the record says how the yes was given.
0.6.9 · Oct 22, 2026 · A seat's report files itself as a receipt and asks nothing; a yes is for Memory. Sentinel reads a seat's quote as a quote.

Every release: CHANGELOG.md.

For builders. MAGNEMO is an MCP server with four verbs — retrieve, stage, bootpack, handoff — plus keep, drop, pending, and a CLI for your side: review, promote, reject. It runs on your machine, in plain markdown files you own. The package imports no network module (magnemo doctor scans for one on every run); the only traffic is git push to a backup destination, if you add one. Every promotion is recorded with who wrote the entry, the name given for the yes, when, and through which gate. Trust is computed from that record, never asserted. It mounts beside any memory you already run (a folder of notes, Obsidian, a RAG stack). Python 3.11+, zero dependencies, Apache-2.0.

Fresh vault? THE CHARTER section will say it isn't promoted yet — that is the governance speaking: MAGNEMO never fabricates canon. Stage a charter, review it, promote it, and every boot thereafter serves it back verbatim. (magnemo not found after install? pip's script folder isn't on PATH — python3 -m magnemo always works.)

Open beta — read [KNOWN_LIMITS.md](KNOWN_LIMITS.md) before trusting it with anything you can't lose. Honest caveats, no fine print.

Install in your client

One server, said ten ways. Every block below is the same thing: uvx magnemo-mcp with MAGNEMO_VAULT pointing at the folder your Memory lives in (make one with magnemo init ./vault). Tested on this Mac where it says so; the rest is from each client's own docs and marked untested — corrections welcome, open an issue.

Claude Code — tested: a Claude Code session mounts the server, lists the seven tools and calls them; a yes in the chat keeps a note, and pending reads a body (last run Oct 28, 2026: Claude Code 2.1.309, the 0.6.11 server).

claude mcp add magnemo -e MAGNEMO_VAULT=/absolute/path/to/vault -- uvx magnemo-mcp

(`claude mcp lis

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

MAGNEMO

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

Install in one paste

Works with

How it compares

What's new

Install in your client