Tool overview
AgentOps is listed under AI Governance Safety & Evaluation AI tools.
What is AgentOps?
AgentOps records agent and LLM activity, visualizes sessions and tool calls, tracks model costs, supports replay debugging and audit trails, and integrates with major agent frameworks through an open-source Python SDK and hosted dashboard.
Best for
Developers and platform teams operating AI agents and LLM applications
Who is it for?
Decision note
Rebuilt from the original export under the complete V412/V411 factual-source-verification workflow. Preview only. Apply remains blocked until Failures = 0, Warnings = 0, Unmapped = 0, Missing = 0; explicit clears are reviewed; image import is disabled or V380 accepts the asset; a representative WordPress edit screen is compared with the export and proposed row; and a post-Apply zero-change Preview succeeds.
Key features
Visual traces for LLM, tool, and multi-agent events
Replay debugging and audit trails
Cost and token tracking across 400+ LLMs
Framework integrations and session export
Use cases
Debugging failed agent runs
Monitoring production agents
Tracking model spend
Auditing prompts, tools, and multi-agent interactions
Pros
- Free tier up to 5,000 events
- Open-source MIT Python SDK
- Broad framework and model integration coverage
Limitations
Observability data can expose prompts, credentials, or customer data if instrumentation is careless.
Teams should redact secrets, restrict access, define retention, and validate agent behavior beyond trace visibility.
Pricing details
Billing options
Pricing note
Basic is free for up to 5,000 events. Pro starts at $40/month with pay-as-you-go scaling; Enterprise is custom.
Supported languages
- English
Integrations
OpenAI Agents SDK
CrewAI
Agno
LangChain
AutoGen
AG2
CamelAI
400+ LLMs and frameworks
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