Dev tools · alternatives · 2026
24 alternatives to Zora
In February, Summer Yue, Meta's director of AI alignment, posted about her OpenClaw agent deleting 200+ emails after she'd told it to wait for approval. She screamed "STOP OPENCLAW" at it. It kept going. The root cause: her constraint lived in the conversation. When the context compacted, it disappeared. The AI hadn't gone rogue; it had genuinely forgotten. Zora's safety architecture is designed so that it can't happen. A few things that are different: Compaction-proof rules. Policy lives in ~/.zora/policy.toml, loaded before every action, not in context. The LLM and the…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 3 we have checked on their own sites, 3 of them free or with a free tier.
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ZooClaw▲290Your proactive team of AI specialists in one place
Apr 2026 · zoowork.ai · its alternatives →
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Context Gateway▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
Mar 2026 · github.com · its alternatives →
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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 · its alternatives →
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CoChat▲261Openclaw for Teams that is secure, collaborative, autonomous
Mar 2026 · cochat.ai · its alternatives →
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Kastrafree tier, from $19.99/mo▲332Hi HN, Fernando and I built Kastra. Kastra intercepts AI agent tool calls and evaluates them against deterministic policies before they execute. We built this product to control pre- and post-inference workloads. This is aimed at developers using coding agents like Claude Code, Codex, Cursor, and OpenClaw. Kastra pushes an allow, hold, and deny decision before the action runs. You can build these policies in plain English from the web app. The interception engine evaluates the tools, targets, and parameters of every action at sub 1ms at a scale of billions of interceptions per day. We also…
Jul 2026 · kastra.ai · its alternatives →
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The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol. Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day. A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship…
Mar 2026 · georgelarson.me · its alternatives →
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com · its alternatives →
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Turn your work activity into structured AI context.
Feb 2026 · claw.toggle.pro · its alternatives →
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Open Index▲89The structured context layer for AI agents. Build self-learning specialised agents that are context aware. - DrDroidLab/open-index
Aug 2026 · github.com · its alternatives →
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026 · yourclaw.cloud · its alternatives →
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JDoodleClaw▲120The most user-friendly OpenClaw. Securely hosted.
Mar 2026 · jdoodle.com · its alternatives →
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Hello HN, I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem). To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills. The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers: Layer 1 (Metadata): Light-weight tags and triggers (always loaded…
Jan 2026 · its alternatives →
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I run OpenClaw agents with access to email, calendar, and files, and kept worrying about them doing things I never actually asked for. ArmorClaw captures intent and cryptographically binds the agent’s tool use to that committed intent. If an agent tries to call a tool outside that plan, it gets rejected. For example, if you ask your agent to ‘email dad asking how he’s doing,’ it should only need your email tool. If it also tries to read your calendar, ArmorClaw rejects that. It’s an open-source OpenClaw plugin, and installation is one command: curl -fsSL…
Apr 2026 · claw.armoriq.ai · its alternatives →
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com · its alternatives →
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An information-flow policy engine for LLM agents.
25d ago · openappa.com · its alternatives →
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Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…
2025 · archestra.ai · its alternatives →
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SafeClawfree tier, from $20/mo▲7Security-first hosting for AI agents
Feb 2026 · safeclaw.tech · its alternatives →
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I’ve been cautiously (and nervously) playing with openclaw and a number of other claw and code agents for a while now, but trying out different ones was tricky so I wanted a simple way to switch out channel ownership… then I wanted more. Security is hard, and I wanted to make it easier. This is FAR from polished, and no claims that I’m a “security expert” but I tried to think and research a bit on different threat models (I think of 2 broad ones for agents, external adversaries and internal agentic failures) and try and offer best in class protection on both, while also not having any…
Apr 2026 · github.com · its alternatives →
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I built a skill library for OpenClaw (always-on AI agent runtime, not session-based) where the agent can teach itself new behaviors during normal conversation. The idea: you tell your agent "every time I ask for a code review, always check for security issues first." It invokes a create-skill skill, writes a new SKILL.md, and that behavior is live immediately — no restart, no config change, no developer required. What I think is actually useful (the safety cluster): • loop-circuit-breaker: OpenClaw retries ALL errors identically. This halts on the 2nd identical failure before it burns your…
Mar 2026 · github.com · its alternatives →
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Hi HN. I've been running AI coding agents (Claude Code, Codex, etc.) on real repos for a while now. The dirty secret of "autonomous coding" is that agents stop all the time — quota limits, test failures, policy violations, bad judgement calls. You end up babysitting them. So I asked a different question: what if the system was designed around the assumption that agents WILL fail, and the job of the infrastructure is to never let that failure become a dead end? openTiger is a "non-human-first" orchestration system that runs multiple AI agents in parallel — planner, workers, testers, judge —…
Feb 2026 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →