Observe · Platform

Agent Registry

One inventory for every agent — see what you have before you evaluate or enforce anything.

Prefactor's Agent Registry gives you a single source of truth for every AI agent in your organisation — who owns it, what framework it uses, what version and environment it's running in, and what tools it can access. No more shadow agents, no more spreadsheet inventories.

Agent registry Illustrative
support-agent-v4 LangChain active
billing-recon CrewAI active
triage-bot Vercel AI staging
legacy-scraper unregistered shadow
TL;DR

The agent registry is Prefactor's inventory of every agent in your organisation — owner, framework, version, and environment — recorded once at registration. It's the identity every other capability (tracing, cost, risk, policy) attaches to, and it's how a shadow agent gets found.

How it works

Agents register three ways. Most teams start with guided registration in the dashboard — add an owner, a framework, and the tools an agent can reach in a short form. Teams shipping through CI/CD register agents directly from a deploy step, using the TypeScript or Python SDK, so every agent enters the registry the moment it goes live rather than after someone remembers to add it.

Neither path catches everything on its own, so the registry also watches for shadow agents — activity from agents that were never registered. When Prefactor sees traffic from an unregistered agent, it surfaces it so the agent can be brought into the same inventory instead of running invisibly alongside the ones you already track.

What the registry tracks

Each entry records ownership and version — who built the agent and which release is running — alongside its framework (LangChain, CrewAI, and the other frameworks Prefactor integrates with natively or via OpenTelemetry), the environment it's deployed in (development, staging, production), and the tools and data it's permitted to reach. Deployment status moves the agent through its lifecycle to eventual retirement or archival, so a decommissioned agent stops showing up as live in dashboards and reports.

Version and environment are what make comparison possible elsewhere on the platform: live tracing and quality assessment both compare an agent's spans across versions and environments to catch drift, and that comparison only works because the registry already knows which version and environment produced each span.

Integration with your stack

Registration is designed to sit inside the deploy step you already have, not add a separate one. Call the registration API from CI/CD using the TypeScript or Python SDK, and an agent registers itself as part of the same pipeline that ships it — no manual step for teams that deploy agents frequently.

Because the registry underpins observability and enforcement alike, it's the first thing to wire up when adopting Prefactor: agent identity, framework, version, and environment are visible from the SDK integration itself, so registration usually needs no extra instrumentation beyond what tracing already requires.

From registry to everything else

The registry is the foundation for every other Prefactor capability. Live tracing and quality assessment compare spans by the version and environment the registry records. Cost attribution uses registry metadata to allocate spend to teams. Runtime policies reference the registry to determine which rules apply to which agents. Audit trails link every action back to the registered agent that performed it. Without the registry, none of the rest has an agent to attach to.

Frequently asked questions

What is an agent registry?
An agent registry is a centralised catalogue of every AI agent deployed in an organisation — who owns it, what framework and version it runs, and which environment it's deployed to. Prefactor's registry is the identity record every other capability (tracing, cost attribution, risk, policies) attaches to.
How do agents get registered with Prefactor?
Two ways: guided registration in the dashboard for exploratory work, or automatically from a CI/CD deploy step using the TypeScript or Python SDK, so an agent registers itself the moment it ships.
What is a shadow agent?
A shadow agent is one running in production that was never registered — often a prototype nobody decommissioned, or a tool adopted without IT's knowledge. Prefactor surfaces shadow agents from the traffic it sees, even if they were never manually added.

Drop this into what you already run

TypeScript and Python SDKs, plus OpenTelemetry ingest — native for LangChain, Claude, Vercel AI, OpenClaw and LiveKit, with 15 framework integrations covered out of the box.

terminal
$ prefactor init

See it on your own agents

Book a demo and we'll walk through agent registry on a fleet like yours — real frameworks, real traces.

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See how every agent performs — and make it better

Prefactor helps teams observe, evaluate, and improve their AI agents in production — across every framework and provider.