XKCD Comic Finder - Find Relevant XKCD Comics

Our XKCD comic finder uses advanced AI and semantic search to analyze your post content and match it with the most relevant XKCD comic from Randall Munroe's extensive collection. Simply paste your text, and we'll find comics that share similar themes, humor, or concepts.

Any text content works! Whether it's social media posts, blog articles, technical discussions, everyday observations, or random thoughts. XKCD covers topics from programming and science to relationships and internet culture, so there's likely a relevant comic for most content.

Absolutely! This tool is perfect for finding XKCD comics to accompany your Twitter, Reddit, LinkedIn, Hacker News, or any other social media posts. A relevant XKCD comic can add humor and relatability to your content.

Yes, as long as the AI API usage does not bankrupt me.

I will regularly retrain the AI model so that it learns and improves. The accuracy depends on the content you provide - more specific and detailed posts typically yield better matches. You can help improve the system by voting on results. Right now, it does miss often.

Try rephrasing your content or adding more context. Sometimes breaking down complex ideas into simpler terms helps find better matches. You can also use the voting system to provide feedback, which helps improve future recommendations.

While this tool is designed to find comics based on your content, you can input keywords or topics (like "programming," "relationships," or "physics") to find comics related to those themes.

I will strive to maintain an up-to-date database of XKCD comics and regularly update it to include new releases. Our collection covers the vast majority of published XKCD comics (anything before August 2025).

Once you find a relevant comic, you can use the copy button to get a direct link to the comic. This makes it easy to share on social media or include in your posts.

No, this is an independent tool created to help people discover relevant XKCD comics. I'm a fan of Randall Munroe's work and have built this tool to make it easier to find and share appropriate comics. All comics remain the intellectual property of Randall Munroe.

It uses Retrieval-Augmented Generation, which is a technique used to more reliably retrieve factual info using AI models. First, a pool of candidate comics is retrieved from a vector database. Then, a Large-Language Model (LLM) is utilised to reason about the content and select the most relevant comic. It is what can enable this to be more than just a simple keyword search if done well.

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