An observability and monitoring SDK built specifically for AI agents - session replays, cost/latency tracking, and error detection across an agent's tool calls and LLM steps, aimed at debugging agents in production, not just in a notebook.
Visit agent This is mine — claim it
Source: https://github.com/AgentOps-AI/agentops
Listing URL: https://www.agentops.ai/
Show your listing is live — the card backlinks here and picks up the verified badge automatically once you claim it.
<iframe src="https://wingmanprotocol.com/embed/card/agentops" width="340" height="170" style="border:0;border-radius:10px" loading="lazy" title="AgentOps — live on WingMan Protocol"></iframe>
Or the one-line script:
<script src="https://wingmanprotocol.com/embed/card.js" data-slug="agentops" async></script>
Or a README badge:
[](https://wingmanprotocol.com/directory/agentops?utm_source=badge)
An ML and LLM observability platform that monitors models and AI applications in production for drift, embedding-space issues and output quality; Phoenix is its
An evaluation platform for AI applications: run a prompt or pipeline change against a test dataset, score the outputs, and track whether quality improved or reg
An ML experiment-tracking platform (logging training runs, metrics and models) that has added Opik, a dedicated tool for tracing and evaluating LLM applications
An evaluation and observability platform for LLM applications that scores production and pre-release outputs for hallucination and quality issues, aimed at catc
An open-source LLM engineering platform for tracing what an application's prompts and agent steps actually did in production, plus tools for prompt management a
An AI evaluation and safety platform that automatically scores an LLM's outputs against test cases for correctness, safety and hallucination, aimed at testing a