Alternatives
Products that do what AgentTrace does
Open-source circuit breaker for AI agent pipelines
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Everything in OpenClaw's terminal, you can now do visually
Apr 2026 · rectify.so
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Your AI agent hits an infinite loop and racks up $2000 in API charges overnight. This happens weekly to AI developers. AgentGuard monitors API calls in real-time and automatically kills your process when it hits your budget limit. How it works: Add 2 lines to any AI project: const agentGuard = require('agent-guard'); await agentGuard.init({ limit: 50 }); // $50 budget // Your existing code runs unchanged const response = await openai.chat.completions.create({...}); // AgentGuard tracks costs automatically When your code hits $50 in API costs, AgentGuard stops…
2025 · github.com
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…
May 2026 · github.com
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Hey HN! Wanted to show our open source agent harness called Gambit. If you’re not familiar, agent harnesses are sort of like an operating system for an agent... they handle tool calling, planning, context window management, and don’t require as much developer orchestration. Normally you might see an agent orchestration framework pipeline like: compute -> compute -> compute -> LLM -> compute -> compute -> LLM we invert this so with an agent harness, it’s more like: LLM -> LLM -> LLM -> compute -> LLM -> LLM -> compute -> LLM Essentially you describe each agent in either a self contained…
Jan 2026 · github.com
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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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We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you. So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly. Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use…
Mar 2026 · github.com
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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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We built meta-agent: an open-source library that automatically and continuously improves agent harnesses from production traces. Point it at an existing agent, a stream of unlabeled production traces, and a small labeled holdout set. An LLM judge scores unlabeled production traces as they stream. A proposer reads failed traces and writes one targeted harness update at a time, such as changes to prompts, hooks, tools, or subagents. The update is kept only if it improves holdout accuracy. On tau-bench v3 airline, meta-agent improved holdout accuracy from 67% to 87%. We open-sourced meta-agent.…
Apr 2026 · github.com
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Local AI agent guardrails, budgets, & circuit breakers.
Jun 2026 · stackmint.ai
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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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Hey HN! I've been wanting to use something like OpenClaw for a while but couldn't get myself to give it access to anything important due to all the risks involved. Prompt injection is still a problem (even though some people seem to ignore it) and so are hallucinations and mishaps that cause agents to do things like delete production data [1]. Even harnesses like Claude Code and Codex are subject to this, particularly since we're getting progressively looser about how we run them e.g. Conductor is really popular and runs agents without any sandboxing. That means we're in a bit of an…
Apr 2026 · agentport.sh
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