Lovable: Six New Connectors — Aikido, GitLab, AWS S3, Hex, Confidence & PostHog
LovableLovable expanded its connector ecosystem with six new integrations across security, DevOps, cloud storage, and product analytics. The Shared Connectors — Aikido, GitLab, and AWS S3 — enable AI-powered penetration testing, two-way repository sync, and direct S3 file access respectively. The Personal Connectors — Hex, Confidence, and PostHog — give the Lovable AI agent access to data notebooks, feature flag experiments, and product analytics for more context-aware development.
Sources & Mentions
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Introducing the Lovable + Aikido Integration for AI-Powered Penetration Testing
Aikido
Lovable adds Aikido, GitLab, AWS S3 connectors
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Lovable's new connectors: Aikido security testing, GitLab sync, AWS S3
Lovable crosses $100M ARR, adds AI-powered penetration testing via Aikido
TechCrunch
Six New Connectors Across Security, DevOps, and Analytics
Lovable added six new integrations in its April 2026 update, split between Shared Connectors (workspace-level integrations) and Personal Connectors (MCP servers that give the AI agent direct access to external tools).
Shared Connectors
Shared Connectors are workspace-level integrations that plug into the app's infrastructure and appear in the Security, Code, and Files views.
Aikido — AI-Powered Penetration Testing
The Aikido connector brings automated security testing directly into the Lovable workflow. Aikido performs AI-powered penetration testing to identify real exploitable vulnerabilities in apps — not just theoretical weaknesses. Security findings are synced to the Security view in Lovable, with downloadable reports that developers can act on immediately.
Aikido tests start at $100 per test, compared to $20,000 or more for traditional manual penetration testing. This makes professional-grade security testing accessible to solo developers and small teams building on Lovable for the first time.
GitLab — Two-Way Repository Sync
The GitLab connector enables two-way repository synchronization between Lovable projects and GitLab repositories. It supports both GitLab.com (cloud) and self-managed GitLab instances, making it suitable for teams in enterprise environments where GitHub may not be the preferred platform. This connector enables code backup, version control, and team collaboration workflows that mirror the existing GitHub integration.
AWS S3 — Direct File Storage
The AWS S3 connector allows Lovable apps to read and write files directly to Amazon S3 buckets. Capabilities include browsing bucket contents, downloading files via signed URLs, and uploading files from the app. This makes it straightforward to build apps with persistent file storage, media uploads, and document management backed by S3.
Personal Connectors (MCP Servers)
Personal Connectors are MCP (Model Context Protocol) servers that give the Lovable AI agent direct access to external data sources during development conversations.
Hex — Data Notebook Access
The Hex connector allows the Lovable agent to query Hex notebooks, bringing data analysis results and computed outputs directly into the development conversation. This is useful for teams that do their data work in Hex and want to build app interfaces around those analyses.
Confidence — Feature Flags and Experiments
The Confidence connector enables the Lovable agent to evaluate feature flags and access experiment configurations. This allows developers to build apps that are tightly integrated with their experimentation infrastructure from the start.
PostHog — Product Analytics
The PostHog connector gives the Lovable agent access to product analytics data from PostHog. Developers can reference usage data, funnel metrics, and user behavior patterns directly in the development conversation, enabling data-driven decisions during app construction.