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AI · alternatives · 2026

24 alternatives to Open Envelope – an open schema for defining AI agent teams

Built an open JSON Schema for defining AI agent teams. Multi-agent systems are becoming a real deployment pattern — not single assistants, but teams with roles, handoffs, and human checkpoints. But there's no shared way to define one that travels across frameworks. Every implementation is scattered, locked to whichever tool you picked first. Built the schema to fix that. The schema lives at schema.openenvelope.org and is registered in SchemaStore, so if you drop a .envelope.json file in VS Code you get autocomplete and validation without installing anything. It's also on npm as…

Open Envelope is an open JSON Schema for defining AI agent teams that work across different frameworks. It standardizes how multi-agent systems with roles, handoffs, and human checkpoints are configured, solving the… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    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 · its alternatives →

  2. 2
    Envelope▲635

    First AI agent for event planning

    2025 · envelope.so · its alternatives →

  3. 3
    Agenta▲362

    Open-source prompt management & evals for AI teams

    Nov 2025 · agenta.ai · its alternatives →

  4. 4

    Hey HN, We’re building OpenJobs AI, an AI recruiting agent focused on the outbound sourcing workflow. In recruiting, teams often already know what kind of person they want — but still spend a lot of time manually searching, filtering, and writing first-touch outreach. We wanted to see how much of that work an agent could actually take over. Today, OpenJobs AI focuses on the sourcing part of recruiting. Given a role, it can help with candidate discovery, filtering, matching, and outreach initiation. The goal is to move sourcing from a manual, repetitive workflow into something an agent can…

    2025 · metix.ai · its alternatives →

  5. 5

    OpenAgents - The collaboration OS for AI agents. Contribute to openagents-org/openagents development by creating an account on GitHub.

    Apr 2026 · open-agents.dev · its alternatives →

  6. 6

    Build no-code agents to target markets untouched by AI

    2024 · its alternatives →

  7. 7
    Clears▲376

    Move beyond AI coding to Agentic Software Delivery

    Aug 2026 · clears.ai · its alternatives →

  8. 8

    Build multi-agent systems with Google's open framework

    2025 · adk.dev · its alternatives →

  9. 9
    Velane▲95

    n8n is built for humans dragging nodes on a canvas. That breaks down at B2B scale (embedding in a product, multi-tenant scalability, etc). n8n does have an MCP server so agents can create workflows too, but it outputs raw JSON. That's fine for n8n's engine, but painful for a coding agent (or a human reviewing its output) to read, write, diff, or debug. I'm building an alternative where workflows are authored by a coding agent in [a more dev-legible format] instead of JSON blobs, and execute it at scale.

    Jul 2026 · velane.sh · its alternatives →

  10. 10
    OpenBox▲171

    See, verify, and govern every agent action.

    Apr 2026 · openbox.ai · its alternatives →

  11. 11
    OpenMolt▲132

    Hi HN! I built OpenMolt, an open-source framework for creating programmatic AI agents in Node.js. Instead of wiring complex workflows (that can break), you define agents in code with instructions, tools, integrations, and memory. The agent then plans steps and executes actions like calling APIs, updating data, or interacting with services. When things break or change, the agent can adapt instead of failing like static workflows. The goal is to make agents behave more like real software systems than prompt scripts. It includes: - a planning/execution loop - tool and API integrations -…

    Mar 2026 · openmolt.dev · its alternatives →

  12. 12

    Author here! Agents are applying to jobs for people right now, with progressively more volume, and there's nothing built for it. So they scrape career pages and fight ATS forms with Playwright/Browser Use, which breaks constantly (or they get bot blocked). Employers get buried in applications that don't fit, candidates hear nothing back, and the resume is now an AI-written thing that another AI scores (which breaks the existing model entirely, btw). OJCP is MCP tools for search and apply, a manifest at /.well-known/ojcp.json so agents can find providers, and schemas that…

    Aug 2026 · ojcp.dev · its alternatives →

  13. 13

    A collection of open-source TypeScript tools by @enmanuelmag. heimdall-mcp for MCP proxy telemetry. agent-harness-kit for multi-agent orchestration.

    May 2026 · ahk.cardor.dev · its alternatives →

  14. 14

    Real-time database schemas for AI-IDEs via MCP protocol

    2025 · schemaflow.dev · its alternatives →

  15. 15

    Hey HN, we're Jon and Kristiane, and we're building Orloj (https://orloj.dev), an open-source orchestration runtime for multi-agent AI systems. You define agents, tools, policies, and workflows in declarative YAML manifests, and Orloj handles scheduling, execution, governance, and reliability. Over the past year we tried to use many different platforms/frameworks to build out agent systems and while building we hit some sort of problem with all of them, so we decided to have a go at it. Jon has worked with kubernettes and terraform for years and always liked the declarative…

    Mar 2026 · github.com · its alternatives →

  16. 16

    Hi HN — I built Superexpert.AI, an open‑source platform that lets you spin up multi‑task AI agents in minutes without writing any code (and lets you extend everything later). What it does - Plug‑and‑play agents – Create agents from a web form. Each agent can contain multiple tasks, and each task can run a different AI model, use its own tools, and follow custom instructions. - First‑class extensibility – Register a TypeScript function with registerServerTool, registerClientTool, or registerContextTool to add new functionality. If you want to share it, publish it as an NPM package and…

    2025 · superexpert.ai · its alternatives →

  17. 17

    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 · its alternatives →

  18. 18

    Generate realistic mock JSON data with AI.

    2025 · schema-ai-ten.vercel.app · its alternatives →

  19. 19

    We recently started to use agents to update some documentation across our codebase on a weekly basis, and everything quickly turned into cron jobs, logs, and terminal output. it worked, but was hard to tell what agents were doing, why something failed, or whether a workflow was actually progressing. We thought it would be more interesting to treat agents as long-lived workers with state and responsibilities and explicit handoffs. Something you can actually see and reason about, instead of just tailing logs. So we built Clawe, a small coordination layer on top of OpenClaw that lets agent…

    Feb 2026 · github.com · its alternatives →

  20. 20

    Hi everyone, I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts. OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them." Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem. So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level…

    Feb 2026 · github.com · its alternatives →

  21. 21
    OpenBot▲36

    Tag specialized agents like friends or employees

    Jun 2026 · getopenbot.com · its alternatives →

  22. 22

    Hi HN! I’m Tony, co-founder of Inngest. I wanted to share AgentKit, our Typescript multi-agent library we’ve been cooking and testing with some early users in prod for months. Although OpenAI’s Agents SDK has been launched since, we think an Agent framework should offer more deterministic and flexible routing, work with multiple model providers, embrace MCP (for rich tooling), and support the unstoppable and growing community of TypeScript AI developers by enabling a smooth transition to production use cases. This is why we are building AgentKit, and we’re really excited about it for a few…

    2025 · github.com · its alternatives →

  23. 23

    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 · its alternatives →

  24. 241D

    We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…

    Jun 2026 · its alternatives →

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