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Argon

by argon-labversion 2.1.4i★ –iRuns on your computer
Registry nameio.github.argon-lab/argon

Install

Overview

Description from the maker (original English)

Versioned MongoDB sandboxes for AI agents: branch, time-travel, merge, and undo over MCP.

PopNx MCP’s three pillars

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

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: Databases & datasets

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).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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": {
    "argon": {
      "command": "npx",
      "args": [
        "-y",
        "argonctl",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add argon -- npx -y argonctl mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "argon": {
      "command": "npx",
      "args": [
        "-y",
        "argonctl",
        "mcp"
      ]
    }
  }
}

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": {
    "argon": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "argonctl",
        "mcp"
      ]
    }
  }
}

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.

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 with the GitHub account argon-lab, 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 Databases & datasetsi

  • More stars than 0% of the other 952 servers in this category
  • Published to the registry more recently than 89% of the other 952 servers in this category
  • Basic checks equal to or better than 100% of the other 952 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 Argon 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?

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 –, and the latest version (2.1.4) reached the registry 4 days ago.

Which apps can use it?

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

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

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

Supabase

by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated today
Install

MongoDB MCP Server

by mongodb-js

MongoDB Model Context Protocol Server

Runs on your computer★ 1,157Apache-2.0Updated 2 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.

Argon — Git for MongoDB

Branch, time-travel, merge and undo your MongoDB. Any driver, real mongod, versioned history underneath. Built for AI agents.

Three ideas, thirty seconds:

  1. A branch is a pointer, not a copy — created with a metadata write. Checkout separately materializes the data.
  2. `checkout` turns a branch into a real MongoDB database — pymongo, mongoose, mongosh, indexes, aggregation, transactions: all real, and supported document writes become history while capture is healthy.
  3. Review and recover changes — diff, merge, undo and pin states within the configured retention and capture guarantees.

Install

For npm, use Node.js 24 LTS with npm 11.16 or newer. The package-scoped approval allows the installer to download Argon's binary on npm 12.

brew install argon-lab/tap/argonctl      # macOS

npm install -g argonctl --allow-scripts=argonctl # cross-platform

MongoDB must run as a replica set (one-node is fine):

docker run -d --name argon-mongo -p 127.0.0.1:27017:27017 mongo:7 --replSet rs0 docker exec argon-mongo mongosh --quiet --eval 'rs.initiate({_id:"rs0",members:[{_id:0,host:"localhost:27017"}]})' argon doctor

Use a current supported MongoDB patch release in production. Source builds use Go 1.26.10 or newer, as declared in go.mod. Use a patched toolchain: Go 1.27.0–1.27.2 also contain October 2026 standard-library vulnerabilities.

The flow

main ──branch──▶ experiment ──checkout──▶ mongodb://…  ← any driver

│ ┌── argon diff ──────────┤ document history ▼ ▼ merge (a data PR) or undo / discard / rewind

# 0 · Stop source writers and DDL for the import — or: argon projects create myapp

argon import database --uri mongodb://localhost:27017 --database myapp --project myapp --source-quiesced

1 · Branch — instant, no copy

argon branches create experiment -p myapp

2 · In terminal A, capture writes with a branch actor label

argon checkout -p myapp -b experiment # prints a connection string argon watch -p myapp -b experiment --actor agent:experiment

In terminal B, write through the printed URI. Then:

3 · Review and merge back — a data pull request

argon diff -p myapp -b experiment argon merge preview -p myapp -b experiment argon merge apply

…or rewind instead of merging

argon restore reset -p myapp -b main --time 2026-07-07T09:00:00Z --backup pre-incident

Prefer clicking? argon console serves a local web console (UI + REST API), supervises capture, reaps expired sandboxes every minute, and opens your browser. The console's MIT-licensed source is in web/; see the rebuild instructions. For a complete managed workflow, run the two-agent pinned dataset example.

What you get

CommandIn one line
Branchingargon branches createa metadata write — instant, zero copy
Real databasesargon checkout / argon proxyany driver, real mongod; proxy serves stable mongodb://host/ ~ URIs
Write captureargon watchexact change-stream images → history, one actor label per branch
Time travelargon time-travel queryquery captured document states at retained LSNs; restore/pin also accept timestamps
Undoargon undo --actor revert a range or actor label; append-only, conflict-aware
Restoreargon restore preview/reset/branchrewind a released branch or fork retained history
Data PRsargon merge preview/applythree-way merges as reviewable plans; conflicts never silent
Sandboxesargon sandbox create --ttl 1hfork + checkout + TTL in one step — disposable agent workspaces
Dataset pinsargon pin create / pin sandboxnamed captured states protected from GC and resets while the pin exists
Web consoleargon consolelocal UI + REST API in one command

Data history covers document inserts, updates, replacements and deletes. Collection drop/rename produces degraded capture; indexes and collection options are not versioned. Native writes are asynchronous; control operations drain capture. Stop writers before release. Existing pins protect their referenced states, while GC can expire audit and undo history. See operations for recovery and credentials.

Storage retention uses snapshots + retention-window GC to keep state plus a window of history, not every write forever. Details and the consistency model, stated honestly: ARCHITECTURE.md.

For AI agents

claude mcp add argon -- argon mcp        # 13 tools: sandbox, diff, merge, undo, pins

Install the published Python SDK and LangGraph adapter.

python3 -m pip install 'argon-agents[langgraph]==0.2.0'

Start argon console --no-browser in another terminal, then:

from argon_agents import ArgonClient, ArgonCheckpointSaver

argon = ArgonClient("http://127.0.0.1:1818") argon.get_or_create_project("myapp") saver = ArgonCheckpointSaver.from_sandbox(argon, "myapp")

Compile and run your LangGraph graph with checkpointer=saver, then review:

plan = argon.merge_preview("myapp", saver.sandbox.branch) print(plan)

After reviewing this exact plan, apply it explicitly:

argon.merge_apply(plan["id"])

Or reject the run: saver.discard()

argon.create_pin("myapp", "eval-v1") # pin the dataset once run = argon.sandbox_from_pin("myapp", "eval-v1") # identical state, every eval run

saver.merge() is a convenience call that previews and applies immediately; use the separate calls above when approval is required. Pins protect captured document state while they exist; keep independent backups.

The full agent workflow: docs/AGENTS.md.

Documentation

Quick startinstall → first merge, step by step
CLI referenceevery command
Agentssandboxes, pins, MCP, REST API, argon-agents, proxy
Architecturehow it works and what it guarantees
Operationsdeployment, chunk stores (S3/FS), GC, v1→v2 migration
Performanceevery number lives in the reproducible benchmarks — none here, by policy

Community

Issues · Discussions · Contributing · argonlabs.tech · Blog


Give your MongoDB a time machine. Branch without fear. ⭐

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