nowfound

AI · June 2, 2026

personal context

Local, portable, + open source context across all LLMs

personal context launched on June 2, 2026 with 4 votes, #3,322 of 22,647 launches that month and more than 75% of that year's launches.

What it does

Tired of rewriting your background for every new AI ? LLM memory features are great, but your context gets trapped inside each platform. Personal Context Engine solves this. It passively interviews you to extract "vignettes" (behavioral scenes, not just labels) and exports your true identity into portable Markdown files. Use the built-in MCP server to connect your local context directly to Claude Desktop or Cursor. No cloud lock-in. Stop the generic AI replies. Own your context.

Does a similar job

all alternatives →
  • Core – open source memory graph for LLMs – shareable, user owned2025 · github.com · ▲112

    I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…

  • AI Context FlowNov 2025 · chromewebstore.google.com · ▲431

    Reusable AI Memory for Smarter Prompts Anywhere

  • Context GatewayMar 2026 · github.com · ▲220

    We 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…

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  • Spydr2025 · spydr.dev · ▲139

    Github for LLM context. One memory, infinite possibilities.

  • ContextPoolApr 2026 · contextpool.io · ▲180

    Persistent memory for AI coding agents

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