AgentOps AI

license

Elastic-License-2.0(app/LICENSE, the AgentOps application)+MIT(OSI, root LICENSE, the agentops SDK)

source

public(SDK + self-hostable app dir)

commercial

app.agentops.ai-SaaS-dashboard-is-the-primary-product

core features withheld

no — app/ ships the whole platform - api, dashboard, clickhouse, opentelemetry-collector, supabase, deploy, landing and compose.yaml - with no ee/ or enterprise directory, no license-key check and no premium flag

AgentOps' application is released under the Elastic License 2.0, which forbids offering it as a hosted or managed service, so the app is source-available rather than open source even though nothing is withheld for a paid tier. The MIT license at the repository root covers only the separate agentops SDK, not this application.

• https://api.github.com/repos/AgentOps-AI/agentops/contents/app recorded 2026-08-12

  The app directory, listed to test whether anything is withheld. It holds LICENSE, README.md, SETUP_GUIDE.md, api, dashboard, clickhouse, opentelemetry-collector, deploy, e2e, graphana, landing, supabase, scripts and compose.yaml. There is no ee/, no enterprise/ and no second license below it. The published tree is the running platform, so on the core_gated question nothing is held back.

• https://github.com/AgentOps-AI/agentops recorded 2026-06-04

  MIT-licensed SDK; complementary SaaS dashboard at app.agentops.ai; self-host option

• https://raw.githubusercontent.com/AgentOps-AI/agentops/main/app/LICENSE recorded 2026-08-12

  Elastic License 2.0, verbatim: "You may not provide the software to third parties as a hosted or managed service". Added in the "AgentOps OSS release (#1190)" commit of 2025-08-09, so the app was published under it.

• https://raw.githubusercontent.com/AgentOps-AI/agentops/main/LICENSE recorded 2026-08-12

  The root LICENSE, which is plain MIT with no carve-out clause of any kind - unlike langfuse, agenta or litellm, it does not name a directory it excludes. It therefore governs the repository root, where the agentops Python SDK lives, and says nothing about app/, which carries its own LICENSE. GitHub's license endpoint reports MIT for the repo on the strength of this file.

• https://raw.githubusercontent.com/AgentOps-AI/agentops/main/README.md recorded 2026-08-12

  The vendor's own claims, recorded including the one the LICENSE contradicts. Under "Open Source": "The AgentOps app is open source under the MIT license. Explore the code in our app directory." Under "Self-Hosting": "Looking to run the full AgentOps app (Dashboard + API backend) on your machine? Follow the setup guide in app/README.md", and the feature table lists "Self-Host: Want to run AgentOps on your own cloud? You're covered". The self-host claim checks out against app/; the MIT claim does not check out against app/LICENSE.

agentops integrates with CrewAI, AG2, the OpenAI Agents SDK, LangChain and Camel, and PyPI downloads of the package are the basis for its adoption reading; GitHub stars on the repository corroborate without setting it. Downloads have fallen from an earlier high, consistent with the stalled release cadence recorded on the capability axis.

• https://github.com/AgentOps-AI/agentops recorded 2026-08-13

  5,771 stars; agent tracing, cost tracking and framework integrations in the README

• https://pypistats.org/packages/agentops recorded 2026-08-13

  Downloads last month 275,111 for agentops (last week 59,009)

AgentOps offers agent execution tracing, cost tracking, session dashboards and integrations with many agent frameworks, but its documentation describes no prompt versioning, datasets or annotation tools, keeping it a step below Langfuse.

• https://docs.agentops.ai/llms.txt recorded 2026-09-29

  Docs index of every page, e.g. "Track and analyze your OpenAI API calls with AgentOps" and "Organize and filter your sessions with customizable tags". Searched the body for evaluation, dataset, prompt versioning and annotation: none.

• https://docs.agentops.ai/v2/concepts/core-concepts recorded 2026-09-29

  Core concepts page: LLM call records include "The estimated cost of the interaction" alongside prompt and completion tokens.

• https://docs.agentops.ai/v2/introduction recorded 2026-09-29

  Docs home: "AgentOps is the developer favorite platform for testing, debugging, and deploying AI agents and LLM apps." with integrations for CrewAI, LangChain and OpenAI Agents and a "Session Waterfall" of LLM calls and tool calls.

• https://github.com/AgentOps-AI/agentops recorded 2026-08-13

  Repository README - "AgentOps helps developers build, evaluate, and monitor AI agents", with a feature table covering step-by-step agent execution graphs, LLM cost management, framework integrations and Self-Host, and an "Evaluations Roadmap" table in which several eval rows are still marked as in-progress rather than shipped.