Recommendations Widget for LinkedIn is a WordPress plugin that enables site owners to manually add LinkedIn recommendations and display them as clean, professional cards. It addresses the need to showcase testimonials from LinkedIn without relying on API access, subscriptions, or external branding. The plugin is delivered through the official WordPress plugin directory and works via shortcode or classic widget.
It provides a simple admin interface where users paste a name, job title, company, recommendation text, and an optional photo URL. Recommendations appear as a horizontal scrolling carousel that functions on both desktop and mobile. Long quotes are clamped to four lines and include a Read more or Read less toggle. Each card can optionally show a View on LinkedIn link. The order of recommendations can be changed through drag-and-drop without editing code. Photos receive smart cropping that anchors portrait images at the top to keep faces in frame, while an initials avatar with color fallback appears when no photo is supplied.
The plugin requires no API keys, monthly fees, or third-party branding. It is intended for WordPress users who want full control over displaying their LinkedIn recommendations directly on their own site. As a no-code tool within the WordPress ecosystem, it integrates through standard shortcodes and widgets.
In the Customer feedback & reputation space, Recommendations Widget for LinkedIn takes a focused approach. Manually publishing and beautifully displaying LinkedIn recommendations on a WordPress site without APIs, subscriptions, or third-party branding. Recommendations Widget for LinkedIn is a consumer product aimed at wordPress site owners and freelancers. Recommendations Widget for LinkedIn is free to use. It runs on the web and embeddable surfaces, and it can be self-hosted.
Behind Recommendations Widget for LinkedIn is Nicola Wright, and it first shipped in 2026. Key capabilities include Admin UI for entries, scrollable carousel, and read more toggle. The interface is available in Bulgarian and English.
Summary written by a language model from the project’s public pages.
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