A swarm of AI agents that hacks like a red team, plus the fix for models that can't tell time

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Gives your AI assistant accurate time and timezone awareness. The model can get the current time in any timezone and convert between them. Simple, but it solves the real problem of models not knowing what time it is. You get current time queries and timezone conversions. No API keys, no external services, runs entirely locally. Completely free. Maintained by the official Model Context Protocol team. A small utility, but surprisingly useful when your AI workflow involves scheduling, deadlines, or coordinating across timezones. Trivial to install, no reason not to have it.

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T3MP3ST points a swarm of AI agents at a target and tries to break in, then writes up how. It automates the red-team loop, reconnaissance, exploitation, and reporting, across web apps, CTF challenges, source code, embedded systems, and smart contracts. Instead of asking for its own API keys, it drives coding agents you already run, Claude Code, Codex, or Hermes. AGPL-3.0 and free. Getting it running is light: npm install, npm run server, and a web War Room interface comes up. What is behind that interface is the honest question. The recon operator is production-ready, but the headline, a coordinated multi-agent swarm chaining exploits end to end, is still largely scaffolded. The benchmark numbers (around 90 percent on a web-security challenge suite, most of a held-out CVE set matched) come from a single agent, not the swarm the name promises. To its credit, the repo ships a verify-claims command so you can re-derive them yourself. This is for security people doing authorized work, pentesters, CTF players, researchers probing their own code, not a push-button tool for anything you do not own. Solo researchers and small security teams: worth a look as an AI-assisted recon and triage layer today, with the exploitation swarm as a promising work in progress. Treat the automation as a force multiplier for a human who knows what they are doing, not a replacement for one. The catch is the gap between the pitch and the product. The recon works, the autonomous kill chain does not fully exist yet, and AGPL-3.0 means anything you build on top inherits that copyleft. Judge it on what runs today, not the roadmap in the README.

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SigNoz puts traces, metrics, and logs in one dashboard, the three pillars of observability you'd otherwise stitch together from separate tools. It's built on OpenTelemetry, the open standard for collecting this data, so your instrumentation isn't locked to a proprietary SDK and works with any compatible backend. The self-hosted version is free and holds nothing back: same codebase as the cloud, every feature included. Running it yourself means running ClickHouse, which is the real ops consideration. ClickHouse is fast but hungry, so plan for a VM with 8GB+ of RAM and storage that grows with your data. Docker or Kubernetes, a couple of hours to stand up. If you have the ops capacity, this is where the savings live. Solo developers: the cloud free tier or a small self-hosted box is plenty. Small teams with ops capacity: self-host. Everyone else: SigNoz Cloud starts at $49/mo for the Teams plan plus usage ($0.30/GB for logs and traces, $0.10 per million metric samples), and it still undercuts a Datadog bill many times over. That's the whole pitch, Datadog-level visibility without the Datadog invoice. The catch is maturity. SigNoz is younger than the Grafana and Prometheus stack, and its plugin and integration ecosystem is smaller. If you need hundreds of prebuilt dashboards and integrations, Grafana still wins. If you want one clean unified platform instead of three tools duct-taped together, SigNoz is the better shape.

The Lens

Home Assistant connects and automates everything in your home: lights, thermostats, cameras, locks, media players, and 2,000+ other device types. Home Assistant ties everything together. Lights, thermostats, cameras, sensors, locks, media players, whatever. One dashboard, one automation engine, running locally on your hardware. Home Assistant integrates with 2,000+ devices and services. It runs on a Raspberry Pi, a NAS, or any Docker host. Everything stays local by default; your data doesn't leave your network unless you choose to send it. The automation engine lets you build rules like "turn off all lights when everyone leaves" without writing code. The largest open source home automation project by a wide margin. Free to self-host. Home Assistant Cloud (Nabu Casa) costs $6.50/mo and adds remote access, voice assistants, and automatic SSL without port forwarding. Anyone interested in smart home automation should try this. The learning curve is real but the community is massive and helpful. The catch: initial setup can take a full weekend. YAML configuration, while being replaced by UI workflows, still shows up in advanced scenarios. And some integrations break after updates; the pace of development is fast, which is both a strength and a source of frustration.