Skip to main content
AgentX-trace-eval is a portable, open-source build of AgentX’s governance layer: Trace, Evaluate, and Monitor, as a single local install. No account, no multi-tenant billing - you bring your own OpenAI, Anthropic, or Gemini keys for judge scoring and semantic detection, everything else runs entirely offline. It’s three pieces working together:
  • Engine - a TypeScript HTTP API (the same Trace/Evaluate/Monitor logic the hosted product runs), compiled to a single native binary so you don’t need Node or Bun installed to run it.
  • CLI (agentx / agentx-server) - a small Go launcher: starts the engine, opens the dashboard, forwards shutdown signals.
  • Dashboard - the real AgentX Governance UI, not a rebuild: AgentX’s own frontend, built in a self-host mode that swaps the login/workspace switcher for a synthetic local user, so it’s genuinely the same interface the hosted product’s Governance page uses rather than a lighter clone.
Get running in a minute with Installation, then wire up Configuration as needed. Every feature page in the Trace, Monitor, Evaluation, and Improve tabs applies to a self-hosted instance; pages marked “Self-host feature” are exclusive to it.

What the dashboard covers

Self-host covers Governance’s Observe tab (traces and sessions, Monitor signals, pattern CRUD, signal triage/feedback), Agents tab (per-agent monitoring profiles, health rate), Overview tab (KPIs strip, trend chart, top-failing breakdown, topic map, Model Comparison, and Judge Calibration), Evaluate’s Runs, Datasets, and Evaluator sub-views (dataset/config CRUD including version history and custom code scorers, viewing run results and judge scores), Monitor’s Online Evaluators, Custom Evaluators, and Topics sub-views (self-host-only, alongside Signals/Patterns, since the backend they call doesn’t exist on the hosted platform), the Improve tab, which shows entirely different content per mode (hosted’s native autotune proposals stay hosted-only, self-host gets Prompt Management and Tool Schemas instead), and a self-host-only Playground tab (see Interactive Playground) for testing prompts/models against a dataset interactively. The two LLM-assisted Monitor features (regex generation, feedback drafting), “create evaluator from signal,” Evaluate’s judge scoring, online evaluators, Topics, a prompt’s or tool schema’s “Suggest improvement,” and Playground all need a provider key set (OPENAI_API_KEY/ANTHROPIC_API_KEY/GEMINI_API_KEY) - code scorers don’t, since they run as plain JavaScript, not an LLM call. The Governance header’s “New evaluation” button is hidden on self-host - it’s built around picking a native AgentX Agent/Team to run, which self-host has no registry for.

Open source scope

The engine, CLI, and SDK are all open source (AgentX-trace-eval, Apache-2.0). The dashboard is the exception: it’s built from AgentX’s own frontend, which stays closed-source. Rather than maintaining a second, lighter dashboard implementation to keep open source, only its compiled build output is published - as a versioned asset attached to AgentX-trace-eval’s own releases - so nobody installing or building self-host, including outside contributors, ever needs access to that private repo. Hosted’s autotune/“Improve” proposal workflow (candidate branch creation, evaluation, merging) follows the same boundary: it’s fundamentally tied to AgentX’s native agent config-branching system, the same “agent building” surface that’s out of scope for self-host - not a missing feature to build later, an explicit non-goal. The Improve tab itself isn’t hidden on self-host, though: it shows Prompt Management instead, self-host’s own answer to “how do I make my agent better.”

Roadmap

  • SDK support for creating/editing code scorers (dashboard-only today)
  • SDK support for creating/editing custom evaluators (dashboard-only today)
  • SDK support for the Tool Schema registry (dashboard-only today)
  • Guardrail (doesn’t exist on the hosted product yet either)

Tracing

What gets recorded on every traced call

Monitor

Automatic detection, patterns, and signals

Custom agent evaluations

LLM-as-a-judge scoring for any agent

AgentX-trace-eval on GitHub

Source, issues, and the full README