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Alternatives

Products that do what Breadcrumb does

Open-source LLM tracing for agent visibility

  1. 1

    A browser that remembers everything and can act on anything

    Jul 2026

  2. 2

    Super-fast web crawling for LLM development

    2024

  3. 3
    TraceLLM100

    OpenTelemetry for production AI applications

    Jul 2026

  4. 4

    Improve your LLM apps with open-source observability tool

    2024

  5. 5
    Twigg157

    Git for LLMs - a Context Management Tool

    Oct 2025

  6. 6

    Trace LLM requests + costs with OpenTelemetry monitoring

    Oct 2025

  7. 7

    Everything you need to evaluate & improve prompts and LLMs

    2023

  8. 8TO

    I built TraceAIO, an open-source tool that prompts LLMs on your behalf and tells you whether ChatGPT, Perplexity, and Gemini mention your brand — and which competitors and sources show up instead. Yeah, this category smells a bit like a grift, same as early SEO. And I think over time it will become just SEO again, and become about good content. The tool just helps you monitor over time. It queries the browser products through real browser sessions, not APIs, runs on Docker, with an MCP server so you can query your own data through an LLM. No business model, Apache 2.0, self hosted. If you…

    Jun 2026 · traceaio.org

  9. 9
    Trails81

    Automated insights from LLM agent runs

    Jan 2026

  10. 10AR

    If you're interested in exploring what LLM-based agent systems these days actually do to solve certain benchmarks such as SWEBench or WebArena, we created a small leaderboard with our team, that allows to view a lot of public and OSS agent results including all the runtime traces (the step-by-step reasoning behind the scenes). Looking at traces is actually quite interesting, as they reveal a lot about the inner working and shortcomings of current agent system, e.g. see https://explorer.invariantlabs.ai/u/invariant/webarena--SteP... for an example trace.

    2024 · explorer.invariantlabs.ai

  11. 11GL

    I wanted to do a complete audit of my AWS account but was dissatisfied with the existing tools. Many of them are clunky to use, and their verbose scan outputs are difficult to understand. So, I built my own open-source tool that uses LLMs to summarize the scan results.

    2024 · guard.dev

  12. 12MY

    LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!

    2023 · github.com

  13. 13LO

    Hey HN, Ola and Karthik here. We are working on Langtrace(https://github.com/Scale3-Labs/langtrace), an open source, open telemetry based SDK and monitoring/evaluations client for LLM based applications. The SDK generates OTEL standard spans and traces for popular LLMs like OpenAI, Anthropic and Cohere, popular frameworks like Langchain and LlamaIndex and vectorDBs like ChromaDB and Pinecone. The LLM monitoring/evaluations space has seen a number of products off late, both open source and closed source ones. But, a couple of things we have observed are: lack of…

    2024

  14. 14GB

    Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…

    2024 · github.com

  15. 15LF

    Hey HN, I built SWE-Kit, LLM toolkit (Function callable tools) which makes building agents specialised in coding like Devin very easy. I noticed a typical pattern while building local agents: creating & perfecting LLM tools to interact with system or codebase was the repeated and time-consuming. We created a layer that simplifies building agents that can interact with code, file system, git, shell and allows you to quickly solve for a wide variety of coding agent use cases. Aren’t there open coding agents already? Well, yes, but most folks would want to solve their specific use case like a…

    2024 · swekit.dev

  16. 16HW

    Hello everyone! I’m thrilled to announce the latest feature from Mutahunter.ai, the ultimate tool for finding and fixing weaknesses in your code. We’ve designed Mutahunter to leverage mutation testing powered by advanced LLMs, helping you uncover vulnerabilities and enhance your code quality effortlessly. Introducing our newest feature: Detailed Mutation Testing Reports! After running our mutation tests, Mutahunter now generates comprehensive reports that clearly summarize: • Vulnerable code gaps • Test case gaps These reports significantly reduce the cognitive load on developers by…

    2024 · github.com

  17. 17

    Check if LLMs can cite your site.

    22d ago

  18. 18OS

    Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

    Oct 2025 · archestra.ai

  19. 19SO

    SURF (Search Utility & Reading Framework) is an open-source API that bridges LLMs with the web. It provides a standardized interface for web search and content processing that preserves formatting of tables, code, and complex layouts. Key features: - Multiple search providers (SearXNG, DuckDuckGo, Brave) - HTML cleaning and smart content extraction - Model Context Protocol (MCP) integration for Claude and other AI assistants - Self-deployable with minimal setup (Docker, bare metal, cloud) - API key authentication I built this to make it easier to add web capabilities to LLM applications…

    2025 · github.com

  20. 20
    lgtmxp2

    Duolingo, but to train the code review muscle

    Aug 2026

  21. 21

    Open-source web scraper — turn any URL into LLM data

    4d ago · gcrawlai.com

  22. 22AI

    Hi I am Jan, CTO @ Pathway. A use case we have been working on with LLMs is to let people know when an answer to their query changes due to revisions of source documents. Obviously, we want to avoid periodically re-computing all queries for the LLM. Why I think it’s cool? - We don’t spin in a loop to repeat with the LLM. - Alerts are LLM-deduplicated - no spamming users with typo fixes - And the best - our framework, Pathway takes care of handling the updates, the example looks nearly like a regular, static RAG chatbot. More context + GIF of how it works for Google Drive document alerts:…

    2023 · github.com

  23. 23UA

    I've been using LLMs for long discovery and research chats (papers, repos, best practices), then distilling that into phased markdown (build plan + tests), then handing those phases to Codex/Claude to implement and test phase by phase. The annoying part was always the distillation and keeping docs and architecture current, so I built Unpack: a lightweight GitHub template plus docs structure and a few commands that turns conversations into phases/specs and keeps project docs up to date as the agent builds. It can also generate Mintlify-friendly end-user docs. There are other…

    Feb 2026 · github.com

  24. 24AC

    Hi HN, we're Ashpreet, Eli and Yash and we're excited to share Phidata: a collection of AI Apps built with open-source tools. While helping teams build AI products, we built templates for spinning up LLM Apps quickly. Today we're open-sourcing our templates for building: - RAG LLM Apps - Autonomous LLM Apps - Multimodal LLM Apps - Data Engineering LLM Apps Templates are built with FastApi for serving, Streamlit for prototyping, PgVector for vectors and PosgreSQL for storage. Run them locally using docker and in production on AWS - with 1 command. - Github:…

    2023 · github.com

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