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Honeystax/OpenClawOpenClaw

🦞OpenClawThe board builders scan before they commit to this stack.

The open-source personal AI assistant ecosystem

OpenClaw is the largest open-source AI assistant platform with 238K+ GitHub stars. Browse the full ecosystem — core alternatives, skills, plugins, memory systems, infrastructure, and desktop apps.

22 featured picks374 builds with real repo pull14 live lanes to scan
833Tracked Builds
2.0MRepo Stars
14Builder Lanes
Read the boardcodeOpen official source
rocket_launch

Fastest Way Into OpenClaw

1. Install

pip install open-interpreter

Requires Python 3.10+. The core runtime for OpenClaw-compatible assistants.

2. Run

interpreter

Opens an interactive terminal session. The assistant can execute code, browse the web, and manage files.

3. Customize

Add skills, connect local LLMs, configure memory systems, and install plugins from the ecosystem below.

code GitHubmenu_book Docspackage_2 PyPI
menu_book

Complete Setup Guide

From zero to your own AI assistant — no experience needed

1download

Install Python

You need Python 3.10 or 3.11 — other versions cause issues

  1. a

    Check your current version

    python3 --version

    If you see 3.10.x or 3.11.x, skip to step 2. If you see 3.8 or 3.9, or "command not found", keep going.

  2. b

    Install Python 3.11

    Mac: brew install [email protected] (install Homebrew first if you don't have it)

    Windows: Download from python.org. Check "Add Python to PATH" during install.

    Linux: sudo apt install python3.11 python3.11-venv

2folder

Set Up a Virtual Environment

Keeps Open Interpreter isolated — skip this and you'll regret it

  1. a

    Create the environment

    python3 -m venv interpreter_env

    This creates a folder called interpreter_env with its own Python. Your system Python stays untouched.

  2. b

    Activate it

    Mac/Linux:

    source interpreter_env/bin/activate

    Windows:

    interpreter_env\Scripts\activate

    You'll see (interpreter_env) in your terminal prompt. That means it's working.

3terminal

Install Open Interpreter

One command — takes about 30 seconds

  1. a

    Install via pip

    pip install open-interpreter

    Make sure your virtual environment is activated first (you should see (interpreter_env) in your prompt).

  2. b

    Verify it installed

    interpreter --version

    You should see a version number. If you get "command not found", try python3 -m interpreter instead.

4key

Set Up Your API Key

Or skip this entirely and use a free local model (step 6)

  1. a

    Get an OpenAI API key

    Go to platform.openai.com/api-keys and create one. You'll need to add a payment method — but costs are low (~$0.01-0.05 per conversation).

  2. b

    Set the key in your terminal

    Mac/Linux (add to ~/.zshrc or ~/.bashrc to persist):

    export OPENAI_API_KEY='sk-your-key-here'

    Windows:

    setx OPENAI_API_KEY sk-your-key-here
  3. c

    Save money with GPT-3.5

    interpreter --model gpt-3.5-turbo

    GPT-4 is the default and costs ~10x more. GPT-3.5 is fine for most tasks. You can also use interpreter --fast as a shortcut.

5play_arrow

Your First Run

Try these to see what it can do

  1. a

    Launch it

    interpreter

    You'll see a chat prompt. Type naturally — it understands plain English.

  2. b

    Things to try

    > What files are in my Downloads folder?> Create a Python script that renames all .jpg files in ~/Photos to include today's date> Make a bar chart of my monthly expenses from expenses.csv> Search Google for the weather in Tokyo and summarize it

    It writes and runs code to accomplish each task. You'll be asked to approve before it executes anything.

  3. c

    Auto-approve mode (skip confirmations)

    interpreter -y

    The -y flag auto-approves all code execution. Only use this when you trust the task — it can modify files and run shell commands.

6computer

Run Locally — Free & Private

No API key needed. Your data never leaves your machine.

  1. a

    Install Ollama

    Download from ollama.com. One-click install on Mac/Windows/Linux.

  2. b

    Pull a model

    ollama pull llama3.1

    Llama 3.1 8B is a great starting point (~4.7GB download). For better results with more RAM, try ollama pull llama3.1:70b.

  3. c

    Run Open Interpreter with your local model

    interpreter --local

    It auto-detects Ollama and uses your downloaded model. Zero API costs. Fully private — nothing leaves your machine.

lightbulbHardware tip: 8B models need ~8GB RAM. 70B models need ~48GB RAM. If your machine struggles, stick with 8B — it handles most tasks well.

7extension

Extend with the Ecosystem

Skills, plugins, memory, and desktop apps

Once you're comfortable with the basics, explore the tools below. The OpenClaw ecosystem includes:

build Skills

Custom commands that teach your assistant new abilities — from web scraping to data analysis.

extension Plugins

Connect to external services — Slack, email, calendars, databases, and more.

memory Memory Systems

Give your assistant long-term memory so it remembers your preferences and past conversations.

desktop_windows Desktop Apps

GUI interfaces that make Open Interpreter feel like a native app instead of a terminal tool.

rocket

Starter Packages

Pick a use case. Get the command. Start building in 60 seconds.

desktop_windows

Desktop & GUI Agent

Control your screen — fill PDFs, manipulate Excel, automate native apps. OS Mode gives the agent eyes and hands via PyAutoGUI + screenshots. macOS: enable Screen Recording in Privacy settings. Linux: install scrot. Single monitor only.

pip install open-interpreter[os] && interpreter --os

Try this

"Open my Downloads folder, find all PDFs from this month, fill in the 'Name' field on each form with 'John Doe', and save them to a new folder called 'filled'"

open-interpreter[os]PyAutoGUIPillowChrome/Edge
code

GitHub Issue → PR

Agent watches your issues board, creates a branch, writes code, runs tests, and opens a PR. The #1 most-requested autonomous workflow on Reddit. Use --loop to keep it running until done. Pair with --safe_mode for guardrails.

pip install open-interpreter && interpreter -y --loop

Try this

"Look at the open issues in this repo, pick the one labeled 'good first issue', create a branch, implement the fix, write a test, and open a pull request"

open-interpretergitpytest/jest--loop flag
lock

Local-First (Zero Cost)

Fully private — nothing leaves your machine. Zero API costs. Requires Ollama + a model download. 8B models need ~8GB RAM. Codestral recommended for code tasks, Llama 3.1 for general use. Fix JSON spam with --no-llm_supports_functions.

pip install open-interpreter[local] && ollama pull codestral && interpreter --api_base http://localhost:11434/v1 --model ollama/codestral

Try this

"Analyze the Python files in this project, find potential bugs, and generate a report — all running locally with no API calls"

open-interpreter[local]Ollamacodestral/llama3.1llamafile
group

Multi-Agent Crew

Team of specialized agents that collaborate via CrewAI — researcher, writer, reviewer, each with defined roles. Requires uv package manager. Windows users need Visual Studio Build Tools for chromadb compilation.

pip install uv && uv tool install crewai && crewai create crew my_project && cd my_project && crewai install

Try this

"Create a crew: researcher finds the top 5 competitors, analyst compares their pricing, writer produces a markdown report with recommendations"

crewaicrewai[tools]chromadbuvlangchain
analytics

Data Pipeline

Chain analysis steps: load data → clean → analyze → visualize → export PDF. The agent writes and runs Python (pandas, matplotlib) autonomously. Use GPT-4o for complex statistical reasoning. Known issue: long outputs get truncated — break tasks into steps.

pip install open-interpreter && interpreter -y --model gpt-4o

Try this

"Load sales_data.csv, remove duplicate rows, calculate monthly revenue trends, create a bar chart for each quarter, and export everything as a PDF report"

open-interpreterpandasmatplotlibGPT-4o
folder_managed

File Automation

Real-time filesystem monitoring with watchdog — auto-sort downloads, rename files, deduplicate, archive old files. Schedule runs periodic maintenance. Use interpreter to generate the watchdog script, then run it standalone.

pip install open-interpreter watchdog schedule && interpreter -y

Try this

"Write me a Python script using watchdog that monitors my Downloads folder, automatically moves .pdf files to ~/Documents/PDFs and .jpg files to ~/Pictures, and runs 24/7"

open-interpreterwatchdogscheduletenacity
auto_awesome

Where OpenClaw is winning

The strongest lanes in this ecosystem, ranked by visible public proof.

Lead builds

hubCore & Alternatives

6 tracked builds

539k ★
Leadopenclaw392k★#2nanobot49k★#3chatgpt-on-wechat42k★#4nanoclaw31k★#5ironclaw13k★#6awesome-openclaw-usecases12k★
Lead builds

buildSkills

6 tracked builds

29k ★
Leadawesome-openclaw-skills22k★#2skillshare2.8k★#3awesome-openclaw-skills-zh1.2k★#4x-research-skill1.2k★#5openclaw-skills1.2k★#6model-hierarchy-skill321★
Lead builds

extensionPlugins

6 tracked builds

17k ★
Leadclawhub9.5k★#2buildwithclaude3.6k★#3dingtalk-openclaw-connector2.1k★#4openclaw-china1.0k★#5openclaw-wechat925★#6openclaw-plugin-wecom251★
Lead builds

psychologyMemory Systems

6 tracked builds

67k ★
LeadOpenViking40k★#2memU15k★#3MemOS11k★#4OpenClaw Supermemory796★#5powermem771★#6MoltBrain252★
Lead builds

dnsInfrastructure

6 tracked builds

84k ★
Lead1Panel37k★#2openfang18k★#3moltworker9.9k★#4ClawWork8.3k★#5ClawRouter6.6k★#6OpenClawInstaller3.4k★
Lead builds

desktop_windowsDesktop & Dashboard

4 tracked builds

13k ★
LeadClawX7.6k★#2VisionClaw2.5k★#3clawra2.4k★#4openclaw-mission-control1.1k★
list

OpenClaw board

(833)

Filter the ranked board by type, timing, and proof signal.

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