--- title: "Supercharging ChatGPT with Kepler: how to give ChatGPT the context it's been missing" url: "https://www.keplerbrowser.com/blog/supercharging-chatgpt-with-kepler" description: "ChatGPT is a brilliant reasoning engine — but it can't see the articles, docs, and videos you come across as you browse. The ChatGPT integration is now live: here's how Kepler gives ChatGPT a memory layer you control, grounded in what you actually saved." --- ChatGPT is one of the best reasoning tools most of us have ever used. Ask it a question and it thinks clearly, writes well, and gets you 80% of the way there. What it doesn’t have — yet — is a persistent, portable view of the things _you’ve come across online_. Every chat starts fresh: it holds some historical chat memory, but the articles, docs, reels, and videos you saw this week live in tabs and bookmarks ChatGPT can’t see. So you paste. A paragraph here, a link there, re-explaining the same background each time. **That’s the gap Kepler fills — and as of now, the ChatGPT integration is shipped and live.** Kepler isn’t another AI model and it doesn’t replace ChatGPT. It gives ChatGPT a memory layer you control: you save links into a space as you browse, Kepler pulls the usable context out of them, and ChatGPT answers questions grounded in what you actually saved. ## What ChatGPT does brilliantly — and where a context layer helps None of this is a knock on ChatGPT. Persistent, curated, cross-tool context simply isn’t what ChatGPT is built around — it’s a reasoning engine first. A few everyday gaps show up as a result: - **Chat memory is light by design.** ChatGPT remembers some facts about you across chats, but it’s not a place to deliberately store and organise the dozens of sources behind a research project. It’s personalisation, not a research library. - **Projects can hold files, but not annotations.** You can upload documents into a Project, but you can’t highlight the three lines that actually matter, and those highlights can’t travel with the source as a relevance signal. - **Memory doesn’t move between tools.** Anything ChatGPT remembers is locked to ChatGPT. Switch to Claude or another model and you start over. A friend uses a different LLM but you want to share memory? Create a shared Kepler space. - **Logged-in and long-form sources fall out.** Content behind a login, or buried in an hour-long video with no transcript, rarely makes it into a chat at all. ## How Kepler solves these Kepler is URL-first. You save the things you find useful — articles, posts, papers, YouTube videos, docs — into a **space** (think: a project folder for context). Each save maps directly onto the gaps above: - **A real research library.** A space is a deliberate, organised home for everything you saved on a topic — not a handful of remembered facts. - **Annotations that carry weight.** Highlight the lines that matter and those highlights become a relevance signal Kepler uses when it extracts context. - **Tool-agnostic by default.** The same saved space works across ChatGPT, Claude, and other AI tools via MCP. Your context isn’t trapped in one product. - **Captures the hard stuff.** For dense sources — a long PDF, a video with no transcript — trigger a deep extract so the detail is captured too. Crucially: Kepler only sees what you choose to save. Connecting a source grants permission; it doesn’t crawl your data. ## Step by step 1. **Create a space** for the thing you’re working on — “Q3 competitor research,” “Japan trip,” “thesis sources.” 2. **Save as you browse.** Use the web extension or mobile share sheet to drop links into the space. Highlight the lines that matter — those highlights become a relevance signal. 3. **Let Kepler pull context.** Each save gets a basic extraction automatically (title, summary, text). For dense sources, trigger a deep extract. 4. **Connect ChatGPT to your space** via the Kepler connection — full walkthrough in [Connect Kepler to ChatGPT](https://www.keplerbrowser.com/help/articles/9291422-connect-kepler-to-chatgpt). 5. **Ask grounded questions.** Now ChatGPT answers from your saved context. ## ChatGPT without Kepler vs. ChatGPT with Kepler **Research synthesis** > _Without Kepler —_ “Summarise the main arguments across the five articles I read on RAG evaluation.” → _“I don’t have access to those articles. If you paste them, I can help.”_ > _With Kepler —_ “Summarise the main arguments across the RAG-eval articles in my Research space, and flag where they disagree.” → _(pulls the five saved sources)_ “Across the five, three argue retrieval quality dominates; two argue annotation/curation matters more. They disagree most on…” **Trip planning** > _Without Kepler —_ “Plan my Japan trip from the stuff I’ve been reading.” → _“I can’t see what you’ve read — tell me the places and I’ll build an itinerary.”_ > _With Kepler —_ “Build a 7-day itinerary from the guides and posts in my Japan space, weighted to the spots I highlighted.” → _(reads your saved guides and highlights)_ “Here’s a route built around the three neighbourhoods you flagged, with the two restaurants you saved slotted in…” **Coming back weeks later** > _Without Kepler —_ a folder of bookmarks you have to re-open and re-read one by one. > _With Kepler —_ “Remind me what I concluded in my thesis-sources space and what’s still unresolved.” → _(reads the annotated set)_ “Your saved sources converge on X; the open question you flagged twice is Y…” Same model. Completely different answers — because it finally has your context. ## Why not just paste? Pasting doesn’t scale and loses the source. Kepler’s context is **tool-agnostic** — the same saved space works across ChatGPT, Claude, and other AI tools via MCP — and it’s **yours**: a curated, annotated set that gets more useful the more you save. ## Get started **Connect Kepler today — it’s free.** Install the extension, start a space, and connect it to ChatGPT — the step-by-step guide is in [Connect Kepler to ChatGPT](https://www.keplerbrowser.com/help/articles/9291422-connect-kepler-to-chatgpt). [Get Kepler](https://www.keplerbrowser.com/get-kepler) to start. Connecting uses MCP, which is **free and unlimited on every tier** — it never costs AI credits. > Kepler helps you create context for AI from the links you save. It improves the AI tools you already use — it isn’t one itself.