nowfound

Alternatives

Products that do what Lookspan does

Local-first observability for AI agents — one command

  1. 1

    One AI gateway with built-in observability and evals

    Jun 2026 · respan.ai

  2. 2

    Open-source runtime for durable AI agents

    May 2026 · orkes.io

  3. 3
    opencode395

    Your terminal's AI agent, with any model you want

    2025

  4. 4

    Observability copilot to resolve production issues instantly

    2025

  5. 5

    AI-powered cloud observability

    2023 · middleware.io

  6. 6

    Real-time observability dashboard for OpenClaw AI agents

    Feb 2026 · clawmetry.com

  7. 7

    Trace LLM requests + costs with OpenTelemetry monitoring

    Oct 2025

  8. 8

    Trace, evaluate, and improve AI agents in production

    Aug 2026 · telerik.com

  9. 9

    Track AI Agents with a single line of code

    Mar 2026 · tracium.ai

  10. 10OD
  11. 11

    Real-time AI coding assistant telemetry in your Mac's notch

    Jan 2026 · github.com

  12. 12
    Foglamp101

    Ship AI agents you can actually see

    Jun 2026 · foglamp.dev

  13. 13

    Improve your LLM apps with open-source observability tool

    2024

  14. 14

    Local tool-calling AI agents with SLMs

    Feb 2026 · onsetlab.app

  15. 15AD

    I've been building computer-use tools for a while, and I quietly launched this about a month ago (122 Stars on GH). I figured it was worth sharing here. Over the last few months, a lot of computer-use agents have come out: Codex, Claude Code, CUA, and others. Most of them seem to work roughly like this: 1. Take a screenshot 2. Have the model predict pixel coordinates 3. Click x,y 4. Take another screenshot 5. Repeat That works, but it's slow, expensive in tokens, and fragile. If the UI shifts a few pixels, things break. And the model still doesn't know what any element actually is. But the…

    May 2026 · github.com

  16. 16

    13,000+ MCP servers, skills & plugins for AI coding agents

    Jul 2026 · codexmarketplaces.com

  17. 17AU

    Agentpanel is an observability platform for optimizing the control flow, performance, token usage, and correctness of LLM/AI agents! Built-in @rustlang, the first release of Agent Panel currently features an AI gateway that provides seamless access to 100+ LLMs across 20+ platforms, including OpenAI GPT-4o, Gemini 1.5 Pro latest, AnthropicAI Claude 3.5, MistralAI, Cohere, Groq,Perplexity AI, and more.

    2024 · github.com

  18. 18
  19. 19RT
  20. 20

    Unofficial Grafana Agent Observability plugin for Hermes Agent - alexander-akhmetov/grafana-agento11y-hermes

    22d ago · github.com

  21. 21RT

    This project (Agents Observe) started as an exploration into building automation harnesses around claude code. I needed a way to see exactly what teams of agents were doing in realtime and to filter and search their output. A few interesting learnings from building and using this: - Claude code hooks are blocking - performance degrades rapidly if you have a lot of plugins that use hooks - Hooks provide a lot more useful info than OTEL data - Claude's jsonl files provide the full picture - Lifecycle management of MCP processes started by plugins is a bit kludgy at best The biggest takeaway is…

    Apr 2026 · github.com

  22. 22

    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

  23. 23OS

    Hi HN, Hugh and Vince here. LLMonitor helps you record, trace & search your LLM queries and chatbot conversations. You can also capture user feedback on your frontend and correlate it with backend LLM queries then use that to fine-tune your own models. The project started has an internal tool in our previous (failed) AI startup. We’re aware the LLM observability space is very crowded. Apart from being open-source, we differentiate with: - Model-agnostic and minimal lock-in (no MITM of requests). - High focus on DX and dashboard clarity. - Support for complex scenarios: e.g. a chatbot that…

    2023 · github.com

  24. 24

    Open-source malware scanner and runtime guard for AI agents

    Jul 2026 · panguard.ai

Ranked by how close each launch is in meaning, then by votes. Refine with a description →