AgentOpsObservability and debugging platform for building reliable AI agents

4.5 (4)

Reviewed by Daniel Nikulshyn·Updated May 2026

Developer Tools Observability Debugging AI Agents Monitoring Analytics SDK

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Overview

AgentOps is a developer platform focused on the lifecycle of AI agents, providing tracing, monitoring, and debugging tools that surface what agents actually do at runtime. It captures LLM calls, tool usage, costs, and errors so teams can understand agent behavior across complex multi-step workflows. Beyond visibility, AgentOps offers session replay, performance analytics, and integrations with popular agent frameworks like LangChain, CrewAI, and AutoGen. This helps engineers move from prototype to production with measurable reliability instead of relying on guesswork or log scraping. It is aimed at developers and teams shipping agentic applications who need to track regressions, control spend, and prove that their agents behave correctly before and after deployment.

Key features

Agent session recording and replay
LLM call and tool-use tracing
Cost and token analytics
Error and failure detection
Framework SDKs for Python and JavaScript
Dashboards for agent performance metrics

Pricing

Model: Free
Category: Observability
Rating: 4.5 / 5 (4)

Use cases

Debug multi-step agent workflows

Use session replay and LLM call tracing to pinpoint where an agent's reasoning or tool use breaks down across complex multi-step runs.

Monitor token usage and costs

Track per-run token consumption and spend across agents to control budgets and identify expensive prompts or inefficient tool calls.

Catch regressions before production

Detect errors and failures in agent behavior during development, helping teams ship agentic applications with measurable reliability.

Instrument LangChain, CrewAI, or AutoGen agents

Drop in Python or JavaScript SDKs to add tracing and performance dashboards to agents built on popular frameworks without custom logging.

Pros & Cons

Pros

Detailed session replay and tracing
Integrates with major agent frameworks
Tracks token usage and cost per run
Useful for debugging multi-step workflows

Cons

Primarily targets developers, not non-technical users
Value depends on framework compatibility
Adds another tool to the LLM stack

Battle record

Across 1 battle in the Pantheon.

1st

2nd

3rd

Last battle

#4
Observability Showdown — July 25, 2026
Jul 25, 2026 · #4 of 9

Reviews

4.5

Average from 4 ratings.

Rina Desai

May 10, 2026

Compared a few options

Evaluated this against two competitors. Where it wins: cost and token analytics and detailed session replay and tracing. On balance the feature set — especially cost and token analytics — justifies the 5 stars for our use case.

Robert Ainsworth

Feb 14, 2026

Does the job

Pretty happy overall. Error and failure detection just works and integrates with major agent frameworks. Primarily targets developers, not non-technical users can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Fatima Zahra

Jan 24, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on cost and token analytics, and tracks token usage and cost per run caught me off guard. Adds another tool to the LLM stack is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Camille Laurent

Jul 24, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is lLM call and tool-use tracing — handled better than most — and useful for debugging multi-step workflows. Worth the time if this is your use case.

Q&A

Can I replay and debug multi‑step agent sessions with AgentOps?

Yes, AgentOps records full session data, enabling point‑in‑time replay of LLM calls, tool interactions, and errors. This time‑travel debugging lets developers step through complex workflows to pinpoint failures or unexpected behavior.

Asked by Kwame Mensah · Oct 2, 2025

How does AgentOps help control token usage and cost for AI agents?

AgentOps tracks token counts and LLM call costs for each agent run, offering dashboards that visualize spend across multiple agents and up‑to‑date price monitoring, so teams can identify expensive calls and optimize budgets.

Asked by Björn Karlsson · Oct 1, 2025

Which agent frameworks does AgentOps integrate with out of the box?

AgentOps provides native SDK integrations for popular Python and JavaScript agent frameworks, specifically LangChain, CrewAI, and AutoGen, allowing developers to capture LLM calls, tool usage, and costs without custom instrumentation.

Asked by Rasheed Osman · Aug 23, 2025

What pricing plans does AgentOps offer and what are the limits of the free tier?

AgentOps has a free tier that includes up to 5,000 events per month with basic tracing and replay features. The Pro plan starts at $40 per month, adding unlimited events, unlimited log retention, export capabilities, and dedicated Slack/email support. Enterprise pricing is custom and adds SLAs, SSO, on‑premises deployment, and advanced compliance options.

Asked by Fernando Rojas · Jul 24, 2025

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