What makes PandaProbe different from traditional observability tools?

PandaProbe is purpose-built for AI agents, offering tracing of LLM calls, MCP calls, tool usage, and custom logic, along with session aggregation and evaluation scoring, which traditional APM tools lack.

Is PandaProbe free to use?

Yes, PandaProbe is open-source and free. The Product Hunt listing shows it as 'Free' and the platform is available on GitHub.

Can I use PandaProbe in production?

Absolutely. PandaProbe supports production monitoring with scheduled recurring evaluations and tracing, helping you detect issues in real-time.

How does PandaProbe handle evaluation?

You can score individual traces and sessions using custom metrics, and set up recurring evaluations to automatically check new data for regressions or quality issues.

Who is behind PandaProbe?

PandaProbe is built by Chirpz AI, a team of PhD researchers specializing in uncertainty and robustness in AI agents, led by founder and CEO Sina Tayebati.

PandaProbe

open source agent engineering platform

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Listed website: pandaprobe.com
Published in directory: May 4, 2026
Last record update: May 4, 2026

Listing information

Overview
5 key features
4 use cases

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What is PandaProbe

PandaProbe is an open-source agent engineering platform that provides deep observability into AI agent applications. It enables developers to trace, evaluate, monitor, and debug AI agents throughout the development and production lifecycle. Built by Chirpz AI and grounded in research, it offers structured tracing, session aggregation, automated evaluation, and production monitoring.

Key Features

Tracing of LLM calls, tool usage, workflow steps, and custom agent logic as structured spans

Session aggregation to understand full agent lifecycle across related traces

Scoring and evaluation to measure quality, reliability, and regression over time

Scheduled recurring evaluations for automated production monitoring

Open-source with community-first development and transparent engineering

Use Cases

AI agent developers debugging complex multi-step agent behaviors in development
ML teams evaluating and monitoring agent performance and regressions in production
Startups building reliable AI agents with production-grade observability and testing
Researchers studying agent robustness and uncertainty using trace-level data

Why do startups need this tool?

Startups building AI agents need robust observability to ensure reliability and quickly debug failures. PandaProbe's open-source nature allows for cost-effective scaling without vendor lock-in, while its evaluation and monitoring features help maintain production quality from the start.