Alternatives
Products that do what Orqisai does
Turn any API into an AI agent. Safely.
- 1AC
api2ai parses OpenAPI Spec to generate an agent that can make API calls. For context, I recently need to explore a handful of API suites and thought LLMs can help expedite this process. After some digging, I found OpenAPI Specs are perfect fit for function calling. Based on a text prompt, api2ai can select the right endpoint and properly parse request params and make api calls. It also handles authentication, currently it supports basic auth, api keys, and bearer token schemes. The tool has helped me explore and see APIs in action without a deep dive into the docs or using postman. It’s open…
2023 · github.com
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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
- 5AH
2025 · github.com
- 6AJ
Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com
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Skip the setup and run OpenClaw & Hermes, fully managed
18d ago · cloudways.com
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- 14TP
Much of my work right now involves complex, long-running, multi-agentic teams of agents. I kept running into the same problem: “How do I keep these guys in line?” Rules weren’t cutting it, and we needed a scalable, agentic-native STANDARD I could count on. There wasn’t one. So I built one. Here are two open-source protocols that extend A2A, granting AI agents behavioral contracts and runtime integrity monitoring: - Agent Alignment Protocol (AAP): What an agent can do / has done. - Agent Integrity Protocol (AIP): What an agent is thinking about doing / is allowed to do. The problem:…
Feb 2026 · mnemom.ai
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2023 · braintrustdata.com
- 17IW
Hey HN, I built browser-use, an open-source alternative to OpenAI’s Operator for browser-use systems, and here’s why I think it’s better: Flexibility: You can use any LLM with our tool – Gemini, Anthropic, Qwen, Llama, DeepSeek, and more. As new models improve, so does your agent. Open Source: No need to pay $200/month or endure long waitlists – it’s free and accessible to everyone today. Custom Automation: Our Python package allows you to build actual web automations. Your LLM can gain new tools, like file uploads. Cost: Our system is 30x cheaper than Operator, e.g., when used with…
2025 · github.com
- 18OA
Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026 · yourclaw.cloud
- 20WB
Hi HN, I'm one of the creators of Nanobrowser, an open-source Chrome extension that lets you automate web tasks using AI agents. We were inspired by the potential of tools like OpenAI's Operator, but we wanted something that was: -Open-Source:You can see the code, modify it, and contribute to the project. -Browser-Based:No complex setups or server deployments. It runs directly in your browser. -Customizable:You can tailor the agent's behavior to your specific needs. -BYO LLM:Bring your own large language model API key (OpenAI, Anthropic,or even local models), No vendor lock-in. -Privacy…
2025 · github.com
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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ArgusAI ▲7AI firewall for LLM calls, MCP tools, and agentic workflows
Jul 2026 · argusai-tau.vercel.app
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