# Signal sources

#### Contents

- Configure sources
- PostHog sources
- External sources
- Search analytics
- Issue trackers
- Support / helpdesk
- Error tracking
- Security scanners
- Product feedback
- Reviews
- What happens next
- Next step

**Open beta**

Self-driving is in open beta. It's improving quickly – expect rough edges, and expect them to disappear fast.

Signal sources are what fill your inbox. A [signal](/content/docs/self-driving/signals/index.html) can be a production error, a support conversation, a Session Replay pattern, a log alert changing state, a Replay Vision scanner finding, an LLM trace regression, an insight anomaly, or an issue from an external tracker. Each source watches one of these streams and turns what it finds into work worth investigating.

## Configure sources

From the inbox, open **settings** and configure your sources. Toggle the ones you want to enable, then follow the authentication prompts for any external services. The inbox is available across surfaces – the [web app](/content/docs/self-driving/web/index.html), [PostHog Desktop](/content/docs/posthog-desktop/index.html), and Slack – and your sources stay the same wherever you open it.

**MCP is handled for you**

You don't need to configure MCP servers for inbox sources manually. Once your repository is connected, research tasks can run automatically.

## PostHog sources

These sources are available when the matching PostHog product has data in your project.

- [Error tracking New exceptions, reopened issues, and error volume spikes.](/content/docs/error-tracking/index.html)
- [Support Actionable items from conversations.](/content/docs/support/index.html)
- [Session replay UX friction, unusual behavior, rage clicks.](/content/docs/session-replay/index.html)
- [Logs Log alerts that fire or break due to threshold breaches.](/content/docs/logs/index.html)
- [Replay Vision Scanner findings, plus each scanner's signal, report, and pull request counts.](/content/docs/replay-vision/index.html)
- [AI Observability Findings from your LLM traffic.](/content/docs/ai-observability/index.html)
- [Product analytics Investigated anomalies from your insights.](/content/docs/product-analytics/index.html)
- [Health checks Outdated SDKs, proxy gaps, ingestion warnings, broken data models, and more.](/content/docs/health-checks/index.html)

**Replay Vision** scanners can send their findings into Signals. Open a scanner to see how many signals it has emitted, how many reports those signals contributed to, and how many pull requests were opened or merged. Reports can combine signals from several scanners and other sources, so these counts show the scanner's contribution, not sole ownership of a report.

## External sources

External sources pull issue context into the same inbox queue as your product signals. Connect any of these via the [data warehouse](/content/docs/data-warehouse/index.html) and the inbox surfaces actionable items for research.

### Search analytics

Search-performance opportunities from connected analytics sources. The inbox identifies pages that rank and receive meaningful impressions but have unusually low click-through rates, then surfaces the query, landing page, impressions, clicks, CTR, and average position for investigation.

- Google Search Console

### Issue trackers

New issues from connected project management and issue tracking tools. The inbox starts a research task to find related code and decide whether a fix is possible.

- GitHub Issues
- Jira
- Linear
- GitLab
- Gitea
- Shortcut
- pganalyze

### Support / helpdesk

Customer support tickets and conversations. The inbox turns actionable bug reports and feature requests into researched implementation work.

- Zendesk
- Freshdesk
- Freshservice
- Front
- Gorgias
- Kustomer
- Dixa
- Plain

### Error tracking

Errors and exceptions from external error monitoring services. The inbox surfaces new errors and error patterns for investigation.

- Sentry
- Rollbar
- Bugsnag
- Honeybadger
- Raygun

### Security scanners

Security vulnerabilities and findings from code scanning tools. The inbox prioritizes actionable security issues.

- Snyk
- SonarQube
- Semgrep
- Rapid7 InsightVM

### Product feedback

Feature requests, ideas, and product feedback from feedback management platforms.

- Featurebase
- Frill
- Aha
- UserVoice
- Productboard
- Canny
- AskNicely
- Retently

### Reviews

App store and product reviews. The inbox identifies actionable feedback from user reviews.

- Appfigures
- AppFollow
- Judge.me

## What happens next

Related signals don't each become their own task. As signals arrive, the inbox deduplicates them and groups related ones, so a signal from a support conversation, a matching error-tracking issue, and a session-replay pattern collapse into a single [report](/content/docs/self-driving/reports/index.html) rather than three. That way you deal with one customer-facing problem, not scattered noise.

Once a report exists, research starts if the source is enabled. The research agent connects it to your codebase, checks user impact, and marks the report as **Actionable** when a code fix is possible.

From there, you can review the report, ask for more research, let an implementation agent open a pull request, or audit the agent log to see exactly what it read and why.

## Next step

See how the inbox researches each report.

[Research tasks](/content/docs/self-driving/inbox/research/index.html)