Alternatives
Products that do what OpenClaw Agent Hub does
Share Agents · Discover Workflows
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Everything in OpenClaw's terminal, you can now do visually
Apr 2026 · rectify.so
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- 11OpenClawCity▲143
A persistent city where AI agents live, create, and evolve
Feb 2026 · openclawcity.ai
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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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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026 · yourclaw.cloud
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Hi HN — I’m building an interoperability layer for AI agents that lets local and remote agents run inside the same network and coordinate with each other. Here is a demo: https://youtu.be/2_1U-Jr8wf4 • OpenClaw runs locally on-device • it connects to remote agents through Hybro Hub • both participate in the same workflow execution The goal is to make agent-to-agent coordination work across environments (local machines, cloud agents, MCP servers, etc). Right now most agent systems operate inside isolated runtimes. Hybro is an attempt to make them composable across boundaries.…
Apr 2026 · github.com
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A curated index of tools powering the OpenClaw ecosystem
Feb 2026
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Practical guides, installation docs, and skills for OpenClaw
Feb 2026 · openclawskill.net
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
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Hey HN, A few months ago, I tried to automate some of my work with the popular AI agent OpenClaw, and then I quickly realized how difficult it is to get it to work with APIs and third-party services securely, which is essential for a lot of work-related tasks. Then I realized OpenClaw is more of a personal assistant and it was not designed to get actual work done as a coworker. So I started to build Valmis, an alternative to OpenClaw that works with more than 100 apps and services, with security being the priority. Valmis addresses the security issue by designing a proxy system: dockerized…
Jul 2026 · github.com
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Hey HN! We've just open-sourced Agent, our framework for running computer-use workflows across multiple apps in isolated macOS/Linux sandboxes. After launching Computer a few weeks ago, we realized many of you wanted to run complex workflows that span multiple applications. Agent builds on Computer to make this possible. It works with local Ollama models (if you're privacy-minded) or cloud providers like OpenAI, Anthropic, and others. Why we built this: We kept hitting the same problems when building multi-app AI agents - they'd break in unpredictable ways, work inconsistently across…
2025 · github.com
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