OpenClaw is everywhere right now, and I get the hype. I’ve been seeing it all over my feed lately, and it’s clearly clicking with a lot of people. 👌
After using it for quite some time myself, it feels a bit too noisy, and not every tool works the same way for every person.
Whenever something starts trending this hard, it’s a good excuse to look around, especially if you’re after something more minimal.
And now, OpenClaw may have its 4th rename to be ClosedClaw very soon. 🤷♂️ You never know with OpenAI.
Why OpenClaw alternatives?
OpenClaw is super powerful, no doubt, but it comes with two big headaches, and you probably have already felt them yourself.
- Security
- Setup Friction
- Security
When your agent can read files, run shell commands, and pull in third-party “skills,” you are basically giving it the keys to your machine. The skill marketplace has already turned into a real problem, with researchers finding hundreds of malicious skills.
If you are not auditing everything you install, it is easy to get yourself cooked.
- Setup Friction
The “self-host it and wire up” path is fun if you like tinkering, but it is also where most people get stuck. You end up handling gateways, background services, tokens, and permission issues (most of the time).
And it's not that you're probably going to use all the features that come with the bloated app, just a few, for most people, so alternatives often could be a good choice.
Below are five OpenClaw alternatives that can cover the same ground, often with a smoother and more minimal experience, depending on what you’re building.
1. TrustClaw
ℹ️ Rebuilt from scratch on OpenClaw's idea with 1000+ tools, with a focus on security.
TrustClaw is for those who like the idea of OpenClaw but don't want to hand over their passwords to the agent and run it locally.
It's built by the Composio team, and the pitch is basically: you get an agent that is available 24/7, capable of taking real actions across a vast number (500+) of apps, but the risky parts like credentials and code execution are handled in a more controlled way.
What makes it different?
- OAuth-only auth: You connect apps the normal way (OAuth), so you are not pasting API keys or passwords into config files.
- Sandboxed execution by default: Every action runs in an isolated cloud environment that disappears when the task finishes. So you are not running “agent code” locally with your permissions.
- Managed tool surface: Instead of pulling random community “skills” from a public registry, TrustClaw uses Composio’s managed integrations and tooling.
- Audit trails + kill switch: It keeps a full action log, and you can revoke access with one click if you ever need to.
The last point is important because agent toolchains are a real security risk right now. These marketplaces, with just one random add-on, can trick you into running malware. This has already happened in the past. Ref: OpenClaw’s AI ‘skill’ extensions are a security nightmare
The kind of prompts it’s built for
-
“Handle my customer complaints and log in Notion”
It finds the right tools, fetches emails, creates drafts, and writes Notion pages (using tools such as:
GMAIL_FETCH_EMAILS,GMAIL_CREATE_DRAFT,NOTION_CREATE_PAGE). “Pull all Reddit threads mentioning [competitor] from the last 3 months, analyze sentiment...”
“Summarize all Slack messages in #product-feedback from this week...”
Why it’s comparatively better (for most of you)
- Setup in seconds (vs. 30 to 60 minutes of tunnels and local setup)
- Encrypted credentials managed by Composio (vs. plaintext local config)
- Remote sandbox (vs. local machine execution)
- Managed tool surface (vs. unvetted public skill registry)
- Action logs + one-click revocation (vs. digging through config files)
- and no need for Mac Mini 🤷♂️
Quick start
- Go to TrustClaw and hit Get Started.
- Connect the apps you want (OAuth flow).
- Give it a task in plain language, or schedule one to run while you are offline.
Here's a demo: 👇
It's that simple, so now you have OpenClaw that runs completely in the cloud with managed permissions and the tools you require.
2. ZeroClaw
ℹ️ Written in Rust, it runs even on $10 hardware with <5MB RAM.
ZeroClaw keeps the agent stack lean. Instead of a big local setup with lots of moving parts, you get a lightweight Rust binary that starts fast and runs comfortably on cheap hardware. If you care more about speed, stability, and low resource use, this one hits the sweet spot.
What makes it different?
- Ultra lightweight: designed to keep CPU and RAM usage low.
- Quick boot: fast startup, good for bots and always-on tasks.
- Modular: swap models, memory, tools, and channels without rewriting everything.
Why pick it over OpenClaw?
- You want something minimal and predictable.
- You’re running on a small VPS / Raspberry Pi / home lab.
- You don’t need a huge plugin marketplace, you need a tool that just runs.
Quick Start
git clone https://github.com/zeroclaw-labs/zeroclaw.git
cd zeroclaw
cargo build --release
cargo install --path . --force
# quick setup with openrouter
zeroclaw onboard --api-key sk-... --provider openrouter
# chat
zeroclaw agent -m "Hello, ZeroClaw!"
3. NanoClaw
ℹ️ OpenClaw's alternative that runs entirely in a container for security.
NanoClaw is basically the same thing but runs completely isolated inside a Docker container. The whole idea is simple: keep the codebase small, and put the risky stuff (bash, file access, tools) inside an isolated container so it can only touch what you explicitly mount.
That's pretty much the idea of NanoClaw.
What makes it different?
- Container isolation by default: runs in Apple Container (macOS) or Docker (macOS/Linux), with filesystem isolation.
- Per-chat sandboxing: each group/chat can have its own memory and its own mounted filesystem, separated from others.
- Built on Anthropic’s Agents SDK: it’s basically designed to work nicely with Claude’s agent tooling and Claude Code.
- WhatsApp + scheduled jobs: message it from your phone, and set recurring tasks that ping you back.
Quick start
git clone https://github.com/gavrielc/nanoclaw.git
cd nanoclaw
claude
Then run /setup. Claude Code handles everything: dependencies, authentication, container setup, and service configuration.
Here's a quick demo: 👇
4. nanobot
ℹ️ Ultra lightweight AI assistant built with Python.
Nanobot, as the name suggests, is quite small. The core agent is about ~4,000 lines of code, and the repo even publishes a live count you can verify with their script. That is the whole vibe: small enough that you can actually read it, trust it, and change it.
What makes it different?
- Core size metric: ~4,000 LOC, with a “real-time” line count shown in the README (and a script to verify).
- MCP support (fresh): added 2026-02-14, so it can plug into MCP tool servers without you reinventing the plumbing.
- Runs where you already are: built-in “gateway” mode supports a bunch of chat surfaces like Telegram, Discord, WhatsApp, Slack, Email, and more.
Quick Start
pip install nanobot-ai
nanobot onboard
nanobot agent # local interactive chat
nanobot gateway # run it as a chat bot (Telegram, Discord, WhatsApp, etc)
Here's a quick architecture:
Here's a video to give you an idea of how it works: 👇
5. memU Bot
ℹ️ Built for 24/7 proactive agents designed for long-running use.
memU Bot is built for people who want an agent that keeps running and becomes more useful over time, instead of resetting to zero every time you open a new chat.
The site definitely looks like it was coded by a 12-year-old 😭, but don’t let that scare you off, because the product underneath is really good.
Under the hood, it’s tied to memU, NevaMind’s memory framework for long-running proactive agents, with a focus on reducing long-run context cost by caching insights.
What makes it different?
- Always-on + proactive: it’s designed to sit in the background and capture intent (not just respond to prompts).
- Memory system that scales: memU treats memory like a file system (categories, memory items, cross-links), so the agent can fetch relevant fragments instead of shoving the whole history into every request.
Quick start
It's a bit more involved than other options.
If you just want the product (memU Bot):
- Go to memu.bot, enter your email, and get the download link they send you.
- Install it like a normal desktop app (they provide a macOS .dmg in the tutorial flow).
- Start it, connect the channel you want (Telegram, etc.), and let it run so it can build memory over time.
git clone https://github.com/NevaMind-AI/memU.git
cd memU
# Requires Python 3.13+
pip install -e .
# set your key (OpenAI is the default in their quick tests)
export OPENAI_API_KEY="your_api_key"
# quick test using in-memory storage
cd tests
python test_inmemory.py
Want persistent memory backed by Postgres + pgvector?
docker run -d \
--name memu-postgres \
-e POSTGRES_USER=postgres \
-e POSTGRES_PASSWORD=postgres \
-e POSTGRES_DB=memu \
-p 5432:5432 \
pgvector/pgvector:pg16
export OPENAI_API_KEY="your_api_key"
cd tests
python test_postgres.py
They also provide a small runnable "proactive loop" example if you want to see the behavior without going through tests:
cd examples/proactive
python proactive.py
There's also a Cloud version which you can try out as well.
It might be worth checking this out: 👇
If you know of any other useful OpenClaw alternative tools that I haven't mentioned in this article, please share them in the comments section below. 👇🏻
That concludes this article. Thank you so much for reading! 🫡
Top comments (2)
OpenClaw is such a flop
Why do you say so?