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The Stack · Roundup

The best observability for AI agents

Tracing, logging, and monitoring for LLM and agent systems. Ranked by community traction, with live GitHub stars and what each is best at.

Short answer: the best observability for AI agents by community traction is Langfuse (★ 33k), followed by Phoenix and Helicone.

✓ Live data verified

1. Langfuse

★ 33k · TypeScript

Open-source LLM engineering platform — tracing, evals, prompt management, and metrics for agent apps. Best for LLM tracing.

2. Phoenix

★ 11k · Jupyter Notebook

Arize's open-source observability for LLM apps — OpenTelemetry-based tracing and evaluation. Best for OTel tracing.

3. Helicone

★ 6.0k · TypeScript

Open-source observability for LLM apps via a proxy — logging, caching, and cost tracking with one header. Best for cost tracking.

Best observability — FAQ

What is the best observability for AI agents?

By community traction, Langfuse (★ 33k) leads the observability in our directory. Open-source LLM engineering platform — tracing, evals, prompt management, and metrics for agent apps.

What is the best open-source observability?

Langfuse is the most-starred open-source option; Phoenix and Helicone are strong runners-up.

Which observability has the most GitHub stars?

Langfuse, at ★ 33k (live count).

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