Alternatives
Products that do what OpenWorkProof does
Cryptographic proof that your AI agent actually did the work
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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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Give AI agents access to real-time data across 200+ apps
May 2026 · apideck.com
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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As AI agents autonomously write and deploy code, there's no standard for verifying that what they shipped actually satisfies business requirements. OQP is an attempt to define that standard. It's MCP-compatible and defines four core endpoints: - GET /capabilities — what can this agent verify? - GET /context/workflows — what are the business rules for this workflow? - POST /verification/execute — run a verification workflow - POST /verification/assess-risk — what is the risk of this change? The analogy we keep coming back to: what OpenAPI did for REST APIs,…
Apr 2026 · github.com
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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…
25d ago · ojcp.dev
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Hi HN, I'm Brian, I spent the last few years at Vanta (YC W18), helping startups and enterprises become compliant and I recently started exploring what that might look like in a post-agentic world. The problem Halo solves is: when a company buys an AI agent from a vendor and gives it access to their data, they have no way to check what the agent did with that data. Vendors may have built observability dashboards and audit logs, but those are editable and partisan. SOC 2 and ISO 27001 audit a company's controls, but controls are less predictive when the software is agentic. TLDR: give an…
Jul 2026 · github.com
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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…
May 2026 · openenvelope.org
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Hi HN, I built Agent Passport, an open-source identity verification layer for AI agents. Think "Sign in with Google, but for Agents." The problem: AI agents are everywhere now (OpenClaw has 180K+ GitHub stars, Moltbook had 2.3M agent accounts), but there's no standard way for agents to prove their identity. Malicious agents can impersonate others, and skill/plugin marketplaces have no auth layer. Cisco's security team already found data exfiltration in third-party agent skills. Agent Passport solves this with: - Ed25519 challenge-response authentication (private keys never leave the…
Feb 2026
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I built an open-source AI agent for security testing to find and fix vulnerabilities in your code. I’ve noticed how bad security vulnerabilities have gotten with everyone shipping AI code slop, so I wanted to build something that allows for vibe-coding at full speed without compromising security. Traditional security tools aren’t effective, and manual pen-testing can’t keep up with the rapidly growing AI code This tool runs your code dynamically, finds vulnerabilities, and validates them through actual exploitation. You can either run it against your codebase or enter your (or someone…
2025 · github.com
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Deterministic offline release evidence for AI agents
Jul 2026 · iisacc-justmoong.github.io
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over this weekend myself and two of my friends took part in a hackathon and built this side-project. we have been diving into computer-use recently and developed an sdk to make it easy to implement for devs like us. one feature we were missing though, was the agent being able to log into services. anthropic understandably blocks this capability with their guardrails, and you wouldn't want your credentials to end up in any model context anyways. so we added a keychain service to the vm that the agent is using. it was built using the pass cli (https://www.passwordstore.org/).…
2025 · github.com
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On-brand AI work that has to prove it is ready to ship
Jul 2026 · corristonconsulting.com
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Hi HN, We’re building security tooling around agentic AI systems. Today, we're releasing our public MCP catalog with detailed risk analysis for every MCP server we've found on the internet: https://mcp.armor1.ai/mcp-directory We all love agents and the power that MCPs unlock: suddenly your AI assistant can query databases, manage files, call APIs, and interact with the real world. But when we started adopting MCPs ourselves, we kept running into the same nagging questions: Is this MCP safe? Where is my data actually going? Could it execute destructive actions? Is it…
Feb 2026 · mcp.armor1.ai
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