AI·rete·RAG
Freemium
Teams needing deterministic rules plus RAG explanations
Kontext
FreeOpen SourceSelf-Hosted
You hit ChatGPT's message limit mid-session, switch to Claude, and spend the next ten minutes re-explaining everything the other model already knew. Kontext-AI is a browser extension built to end that re-explanation loop.
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Get This Tool
License: MIT Any use incl. commercial
Local-run terms: Run the open-source Chrome extension locally under MIT license with full modification and commercial use rights.
Pricing
- Model
- Free
Summary
Kontext captures the full conversation from ChatGPT or Claude via the page's internal API, runs an on-device summary using Gemini Nano or a user-supplied API key, and places a formatted handoff prompt into the target AI's input field — without sending anything to an external server. The workflow is one-click once installed. The tool is MIT-licensed, open-source, and the vendor states nothing leaves your machine. The ceiling appears fast: there is no multi-turn session management, no persistent storage of prior kontexts, and no support for AI platforms beyond ChatGPT and Claude. Teams running workflows across three or more models, or needing a searchable archive of past sessions, will hit that boundary quickly.
Bottom line: Kontext-AI is the right pick for a developer who regularly bounces between ChatGPT and Claude and wants a zero-account, privacy-safe way to carry context across — it breaks down the moment you need to do the same across a third model or pull from a session you exported last week.
Find your fit
Before you choose Kontext
More options in Inference Engines & Infra. Compare pricing, platforms, and features side by side.
Agentmetry
Free · Open source
SOC and DevSecOps teams
Pros
- On-device summarization via Gemini Nano, so conversations containing proprietary code or sensitive research never leave the local machine — eliminating the cloud-data exposure that affects browser extensions relying on remote APIs.
- Full-fidelity conversation capture before distillation, which means the handoff prompt carries the actual reasoning thread rather than a lossy paraphrase — reducing the back-and-forth needed to re-orient the receiving model.
- Never auto-sends to the target AI, so you review and edit the pre-filled prompt before anything is submitted — catching context errors before they propagate into the new session.
- MIT-licensed with an open GitHub repo, so teams with specific capture or formatting requirements can fork and modify without waiting on a vendor roadmap.
- Zero-account, local-first operation, which means there is no authentication surface to manage and no account data to breach — a real difference for individual researchers avoiding cloud context storage.
Cons
- Platform support is limited to ChatGPT and Claude at the source level. The moment your workflow involves a third model — Gemini, Mistral, a local Ollama instance — the tool does nothing. Teams in that position manually export transcripts or write their own bridging scripts.
- There is no persistent kontext storage or retrieval. A session captured and handed off leaves no searchable record inside the tool. Users who need to return to a past session days later must have saved the distilled output themselves; the extension has no memory of prior captures. Teams with audit or reproducibility requirements manage this with external note tools, which eliminates most of the one-click convenience.
- The project shows 9 stars and 1 fork at the time of scraping, with no open issues or pull requests. The bus-factor risk is real: there is no community responding to bugs, no changelog cadence, and no indication of maintained compatibility with ChatGPT or Claude UI changes. Teams that depend on this for production workflows will find themselves forking and patching when either platform updates its internal API structure — at which point they own the maintenance burden entirely and typically replace the tool with a more actively maintained alternative.
About
- Platforms
- Chrome
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- July 5, 2026
Best For
Who it's for
- Users frequently switching between ChatGPT and Claude
- Privacy-conscious individuals avoiding cloud context storage
- Developers or researchers building on extended AI dialogues
What it does well
- Transferring long ChatGPT conversations to Claude when hitting message limits
- Moving context between models without re-explaining history
- Maintaining full-fidelity records of AI coding or research sessions
Integrations
Frequently Asked Questions
- Is Kontext free?
- Kontext offers a free option. Hosting, model usage, or optional services may have separate costs; check the pricing details and official terms.
- Is Kontext open source?
- Yes. Kontext is open source.
- Can I self-host Kontext?
- Yes. Kontext supports self-hosting on your own infrastructure.
- What platforms does Kontext support?
- Kontext is available on: Chrome.
Curated lists that include this category
Kontext-AI is a browser extension that intercepts your active ChatGPT or Claude conversation, distills it into a portable summary called a ‘kontext’, and pre-fills the input field in the other AI so you can continue without re-explaining history. The core workflow is three steps: capture the chat, distill it on-device, and hand it off. The vendor states the tool uses Gemini Nano running locally for summarization, with the option to supply your own API key. No account is required, nothing is transmitted to a remote server, and the handoff never auto-sends — you review before anything goes to the model.
The differentiating feature is the local-first summarization. Where most context-bridging approaches either paste raw transcript (blowing through token limits) or depend on a cloud backend to compress it, Kontext uses on-device inference for the distillation step. For privacy-conscious users or anyone working with sensitive research or code sessions, this means the conversation never touches infrastructure outside the browser and the local machine.
The tool fits a narrow but real use case: single-user, two-model context transfer, primarily for long coding or research sessions that bump into platform message limits. It breaks outside that scope. Platform support is limited to ChatGPT and Claude — adding a third model requires a code contribution, not a settings toggle. There is no built-in storage or retrieval of past kontexts, so a session captured on Monday cannot be recalled on Friday without the user having saved the output manually. Teams that need a searchable history of AI sessions, or that work across more than two platforms, will need a different architecture entirely and are likely to migrate to a more full-featured session management tool.
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