Comparison

Agentry vs Sentry

Both capture errors. Sentry is built for a human-facing dashboard you open to triage; Agentry is built for an AI coding agent that triages and fixes errors directly in your editor. Use whichever matches how your team actually debugs.

TL;DR

Pick Sentry if

  • Your team has a dedicated SRE/on-call rotation reading a dashboard daily
  • You need 10+ years of battle-tested SDKs across 20+ frameworks
  • You're already on Sentry and the integration cost outweighs the agent-first benefits
  • Compliance/procurement requires a Fortune-500-listed vendor

Pick Agentry if

  • You debug from Claude Code / Cursor / Codex — the dashboard is friction
  • You want errors + analytics + deploys in one product, agent-investigated
  • You're building greenfield and don't want to ship an SDK
  • "Just ask the agent what broke" sounds better than "open the Sentry tab"

Feature comparison

Capability Sentry Agentry
Error capture + grouping Yes — 30+ SDKs Yes — raw HTTP POST (no SDK)
Stack unmangling (sourcemaps) Server-side, opaque Local in MCP, reviewable in node_modules
Investigation surface Web dashboard Agent in your editor (MCP)
Product analytics (funnels, retention) Limited (separate product) First-class (HogQL)
Deploy attribution Releases (manual setup) First-class, auto-correlated
Session replay Yes (separate paid SKU) Yes (PostHog-backed, included)
Feature flags + A/B tests No Yes
SDK install required Yes No — ~25 lines of fetch
Public-shareable dashboards Internal only Yes (CORS-open, agp_ key)
Pricing model Per-event tiers, gets expensive at scale Free during beta, usage-based later
Setup time ~1 hour (SDK install + sourcemaps + releases) ~5 minutes (one prompt to your agent)

When Sentry is the right call

Sentry is the right tool when your debugging workflow already centres on a shared dashboard that on-call engineers and customer support open multiple times a day. The volume of mature SDKs (Python, Java, .NET, mobile native, etc.) is hard to match — if you're shipping in a framework that's been around since 2014, Sentry probably has a plug-and-play integration. The web UI's triage features (assignments, comments, status workflows, Slack integration) are mature.

Stick with Sentry if your team's debug ritual is "open the dashboard, find the issue, click resolve." Switching to agent-first debugging is a cultural change as much as a tooling one.

When Agentry is the right call

Agentry is the right tool when your team already lives in an AI coding agent (Claude Code, Cursor, Codex, Cline, Windsurf). In that workflow, opening a separate dashboard is friction — you want to ask the agent "what broke after my last deploy?" and have it investigate, query analytics, read the case, and draft the fix in the same conversation it's already in.

Agentry also wins when you want errors + analytics + deploys in one product. Sentry sells these as three SKUs; Agentry treats them as the same data plane, queryable in the same prompt. The deploy-regression recipe illustrates: one prompt diffs error fingerprints around the latest deploy and tells you what's new — Sentry can do the diff, but only in the dashboard.

And if you're building greenfield without an SDK install already in place: Agentry's no-SDK design is meaningfully simpler.

Migrating from Sentry

Agentry's /v1/store/<project_id>/ endpoint accepts the Sentry wire protocol — your existing SENTRY_DSN environment variable becomes AGENTRY_DSN, and most unofficial transport code keeps working. You don't have to migrate all at once; dual-write to both for a week, compare what you get, then cut over.

These recipes cover the Sentry use cases most teams care about:

Try Agentry against your real data.

Dual-write for a week. Compare. Switch if it's better. The agent handles install — you just paste one prompt.

Install https://agentry.sh/agentry.md and set it up
Agentry vs PostHog → Agentry vs Mixpanel → Agentry vs Datadog → Agentry vs Amplitude → Agentry vs LaunchDarkly → Agentry vs LogRocket → Agentry vs Highlight.io →