
ContextCut PRO
Private AI that injects your knowledge into every LLM query
ContextCut PRO launched on May 17, 2026.
What it does
ContextCut PRO — A local AI privacy layer that injects your knowledge base into every LLM query. No cloud, no telemetry, no data leaving your machine. Works with any OpenAI-compatible client. Dropmd files into the knowledge folder, auto-ingested by watcher. Real token savings (60-80%) visible per query. Starter packs for lawyers, CPAs, doctors included. $99 lifetime, 3 seats. Stop wasting tokens. Inject only what matters. Buy on Gumroad (https://5984630877416.gumroad.com/l/ContextCut-Pro)
Does a similar job
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Context GatewayMar 2026 · github.com · ▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
- IBI built a more productive way to manage AI chats2025 · contextch.at · ▲162
I released ContextChat, an AI chat designed to be context-centric, helping you stay focused and productive by giving you control over the information your AI sees. You can import websites, files, and public/private GitHub repos to give the AI full knowledge of your projects. Unlike other chatbots, ContextChat lets you easily switch between project contexts, so you get relevant answers and avoid the noise. It's pay-per-use, giving you flexibility and control over costs and free models are available so you can try it for free with no monthly subscriptions. Let me know your feedback!

Whisper Internet Infra AI ContextMay 2026 · whisper.security · ▲95Free MCP for security AI: live BGP, DNS, threat graph

AgentReadyFeb 2026 · agentready.cloud · ▲118Compression API that reduces prompt size by 40-60% before sending to your LLM. Your API key never leaves your environment.
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Source: Product Hunt launch ↗
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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