Alternatives
Products that do what openclaw-sdk does
The Python SDK that makes OpenClaw agents production-ready
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I’ve been running Clawdbot for the last couple weeks and have genuinely found it useful but running it scares the crap out of me. OpenClaw has 52+ modules and runs agents with near-unlimited permissions in a single Node process. NanoClaw is ~500 lines of core code, agents run in actual Apple containers with filesystem isolation. Each chat gets its own sandboxed context. This is not a swiss army knife. It’s built to match my exact needs. Fork it and make it yours.
Feb 2026 · github.com
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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We are Bailey and Robbie and we are working on Klaus (https://klausai.com/): hosted OpenClaw that is secure and powerful out of the box. Running OpenClaw requires setting up a cloud VM or local container (a pain) or giving OpenClaw root access to your machine (insecure). Many basic integrations (eg Slack, Google Workspace) require you to create your own OAuth app. We make running OpenClaw simple by giving each user their own EC2 instance, preconfigured with keys for OpenRouter, AgentMail, and Orthogonal. And we have OAuth apps to make it easy to integrate with Slack and Google…
Mar 2026 · klausai.com
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Hi HN, I’m the creator of pycoClaw. I wanted to run OpenClaw-class, platform-agnostic, autonomous agents on MicroPython hardware, but standard tools couldn't handle the scale of the task. pycoClaw is the result, which bridges the gap between high-level AI reasoning and bare-metal execution. The Stack: - PFC Agent (~26k LOC): A full-featured agent that uses an LLM to 'self-program' its own local MicroPython scripts. Once a task is solved, it runs locally without requiring the LLM. - ScriptoStudio IDE: A PWA https://scriptostudio.com designed for the iteration speed required by…
Mar 2026 · pycoclaw.com
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026
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2022 · openziti.io
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I built DevClaw, an OpenClaw plugin that turns each Telegram group into an isolated, autonomous dev team: planner/orchestrator, DEVs, and QA all running on their own. I use it for all my development now. Issues on GitLab/GitHub are the single source of truth, and three things compound to save around 70% on tokens: model tiering (Haiku for typos, Opus for architecture), session reuse across tasks, and token-free scheduling that burns zero LLM calls for orchestration. Please try it and give some feedback. Also keen to hear from anyone running autonomous coding agents, especially what…
Feb 2026 · github.com
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