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🤖AutomatisationIntermediate6 steps

OpenClaw: open-source autonomous AI agent framework

OpenClaw has become the open-source reference for autonomous AI agents in just a few months, with over 250,000 GitHub stars. The framework runs locally on your machine or server under an MIT license, with zero vendor lock-in. Its ClawHub ecosystem gathers 13,000+ reusable skills and offers native integrations with Telegram, Discord, Slack and WhatsApp. The project, launched by Peter Steinberger (hired by OpenAI in February 2026), embodies the self-hosted AI agent trend. For developers seeking a serious alternative to proprietary agents, OpenClaw delivers a rare balance: full autonomy, extensibility via skills, and privacy since everything runs on your own infrastructure.

open-sourceautonomousself-hostedclaudemitskillsclawhubagent-ia

For who

Developers, technical teams, AI tinkerers, and data-sovereignty-focused companies who want a powerful AI agent without cloud dependencies.

Input

Type: text
Format: structure

Instructions en langage naturel, skills ClawHub selectionnes, cles API LLM, configuration d'integration (Telegram, Slack, etc.).

steps (6)

1

Prerequisites and install

info

Install Docker, Git and Node.js 20+. Clone the OpenClaw repo and run the install script to set up the local environment.

2

Configure API keys

info

Set LLM API keys (Anthropic, OpenAI, or local model via Ollama) in the .env file.

3

Install skills from ClawHub

info

Browse ClawHub and install skills matching your use cases (web search, file operations, code execution, etc.).

4

Connect an interface

info

Configure Telegram, Slack, Discord or WhatsApp integrations to chat with your agent from your existing tools.

5

First run and iteration

info

Launch the agent, observe its behavior on a simple task, then iterate by adding skills and custom system instructions.

6

Deploy to production

info

Host OpenClaw on a VPS or 24/7 local machine. Enable logs, persistence and backups.

Output

Type: text
Format: libre

Reponses de l'agent autonome : actions executees, resultats structures, fichiers generes et messages envoyes via les interfaces connectees.

Example

Input

Goal: "Watch new GitHub issues on acme/backend daily, summarize those tied to 500 errors, and post the summary to Slack channel #dev-ops."

Output

OpenClaw installs the github-watcher and slack-poster skills from ClawHub, schedules a cron job, filters issues by label and keywords, and posts a structured summary to Slack every morning with direct issue links.

Customization

ParameterDescriptionDefault
Modele LLMChoix du fournisseur LLM (Anthropic Claude, OpenAI GPT, ou modele local via Ollama).Claude Sonnet
Skills installesListe des skills ClawHub actives sur l'agent, selon les cas d'usage vises.web-search, file-ops, code-exec
InterfaceCanal de communication principal avec l'agent (CLI, Telegram, Slack, Discord, WhatsApp).Telegram

Technical Notes

Requires Docker and at least 8 GB RAM to run heavier skills. MIT license. Costs limited to LLM calls billed by your provider.