nowfound

Alternatives

Products that do what MetricBase does

The ops workspace you burn tokens for — not subscribe to

  1. 1

    Build the semantic layer that makes AI analytics trustworthy

    Mar 2026 · metabase.com

  2. 2

    Fully integrated analytics from Supabase. Free to use.

    2025

  3. 3
    Recost130

    Your API costs fully visible.

    Apr 2026 · recost.dev

  4. 4

    Self-hosted analytics with session replays, heatmaps & more.

    2020

  5. 5

    Hosted server side tagging auto configured in <15 minutes

    2024

  6. 6
    Openbase216

    Manage your team of AI agents by voice, from anywhere

    Jul 2026 · openbase.cloud

  7. 7CA

    Built this after realizing I was spending ~$1400&#x2F;week on Claude Code with almost no visibility into what was actually consuming tokens. Tools like ccusage give a cost breakdown per model and per day, but I wanted to understand usage at the task level. CodeBurn reads the JSONL session transcripts that Claude Code stores locally (~&#x2F;.claude&#x2F;projects&#x2F;) and classifies each turn into 13 categories based on tool usage patterns (no LLM calls involved). One surprising result: about 56% of my spend was on conversation turns with no tool usage. Actual coding (edits&#x2F;writes) was…

    Apr 2026 · github.com

  8. 8
    Workbase193

    Use formulas to power dynamic alerting and actions

    2021

  9. 9

    Strava for your coding assistants

    Apr 2026 · edgee.ai

  10. 10

    An open source analytics client for Supabase database

    2022

  11. 11
    CodeBurn103

    See where your AI coding spend actually goes

    26d ago · codeburn.app

  12. 12

    Spotify Wrapped for Claude, Codex & a Public leaderboard.

    Jun 2026 · whoburnedmore.com

  13. 13

    Usage, cost, and behavior tracking for AI coding agents

    Jul 2026 · tokenbasehq.com

  14. 14IM

    TLDR: I made a public only web analytics without signup. Stores views and visitors for 10 days before deleting data. Exactly 25 days ago today I posted here, proud of my new web analytics. The response was mixed and my post even got flagged (understandable). It was my first real launch and I actually made a sale just a day later of 49$(!). Back then my project was pay once, keep forever. Since then I have sadly went over to the dark side (subscription based). Anyways, I never went back to look at the post after the first two hours, turns out I got a lot of answers. Most answers was something…

    2024 · indielytics.link

  15. 15

    I wanted to share a project I’ve been working on called Frugal Tokens. I originally built it because I was curious to see how much all of my sessions cost and how much cache misses affected that spend. I’d noticed people had widely different spend profiles and wanted to better understand what might contribute to that. As I’ve worked on this, the tool has grown to show more usage patterns across all of your sessions. It shows overall usage, estimated working time and overlapping sessions, and where your spend is coming from across models and cache misses. I also have a few session level…

    18d ago · demo.frugaltokens.com

  16. 16CA

    I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!

    Sep 2025 · infrastructureas.ai

  17. 17AU

    Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT&#x2F;Claude&#x2F;etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https:&#x2F;&#x2F;yolo-auto.com. Here are…

    Jul 2026 · yolo-auto.com

  18. 18

    Self-hosted MRR dashboard for indie hackers

    Jun 2026 · metricmint-app-production.up.railway.app

  19. 19TT

    I use multiple AI tools for work and also my side projects, and the annoying part was to track my costs and token usage across tools. Everytime I had to visit each tool and its respective usage setting to check it and I was losing patience and also was getting hit by surprise limits Now I know that there are already free&#x2F;open-source trackers for Cursor or Claude usage, and they are useful if that is all you need. My problem is broader as I wanted one small place to see tokens, spend, subscriptions and limits across the AI tools I actually use. I was really tired of switching tabs and…

    Jul 2026 · lifehacksgermany.com

  20. 20CS

    Hi HN! Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests &#x2F; responses as much as possible. But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo&#x2F;context? People usually accumulate skills, agents, MCP servers,…

    Jun 2026 · github.com

  21. 21

    See what your AI coding agents think, cost and do

    Jul 2026 · tokentelemetry.com

  22. 22LC

    Hi HN, I'm building Librarian (https:&#x2F;&#x2F;uselibrarian.dev&#x2F;), an open-source (MIT) context management tool that stops AI agents from burning tokens by blindly re-reading their entire conversation history on every turn. The Problem: If you're building agentic loops in frameworks like LangGraph or OpenClaw, you hit two walls fast: Financial Cost: Token usage scales quadratically over long conversations. Passing the whole history every time gets incredibly expensive. Context Rot: As the context window fills up, the LLM suffers from the "Lost in the Middle" effect. Response latency…

    Feb 2026 · uselibrarian.dev

  23. 23

    Hey HN - there are lots of tools to understand how many tokens you use and how much it costs, but we haven't found any that tell you where those tokens are going! Decant helps you understand what you are spending tokens on (context gathering, planning, code, chat, etc), so you can optimize it.

    25d ago · github.com

  24. 24SO

    hello everyone, my first post! AA here, founder of ⌘ Langbase.com — we are a developer platform for building and scaling serverless AI memory agents. I know surveys can be boring, but this one’s different—it’s interactive! That's very much intentional. My team and I have been up for the last 21 hours putting together this report. This was a looot of work, so I hope y'all like it. Introducing … State of AI Agents 2024 report On Langbase, we processed 184 billion tokens and handled 786 million AI agent runs from 36K developers. From all that data plus insights from 3.4K builders who filled out…

    2024 · langbase.com

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