Linggen – A local-first memory layer for your AI (Cursor, Zed, Claude)
Hi HN, Working with multiple projects, I got tired of re-explaining our complex multi-node system to LLMs. Documentation helped, but plain text is hard to search without indexing and doesn't work across projects. I built Linggen to solve this. My Workflow: I use the Linggen VS Code extension to "init my day." It calls the Linggen MCP to load memory instantly. Linggen indexes all my docs like it’s remembering them—it is awesome. One click loads the full architectural context, removing the "cold start" problem. The Tech: Local-First: Rust + LanceDB. Code and embeddings stay on your machine. No…
In plain words
Linggen is a local-first memory layer that indexes documentation and project context for use with AI coding assistants like Cursor, Zed, and Claude. It stores code embeddings and indexed documents on your machine without requiring accounts, and integrates via VS Code extension and MCP protocol. The tool helps developers avoid repeatedly explaining complex multi-project systems to LLMs by loading architectural context in a single click, while also providing visibility into file dependencies and supporting team knowledge sharing.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, Working with multiple projects, I got tired of re-explaining our complex multi-node system to LLMs. Documentation helped, but plain text is hard to search without indexing and doesn't work across projects. I built Linggen to solve this. My Workflow: I use the Linggen VS Code extension to "init my day." It calls the Linggen MCP to load memory instantly. Linggen indexes all my docs like it’s remembering them—it is awesome. One click loads the full architectural context, removing the "cold start" problem. The Tech: Local-First: Rust + LanceDB. Code and embeddings stay on your machine. No accounts required. Team Memory: Index knowledge so teammates' LLMs get context automatically. Visual Map: See file dependencies and refactor "blast radius." MCP-Native: Supports Cursor, Zed, and Claude Desktop. Linggen saves me hours. I’d love to hear how you manage complex system context! Repo: https://github.com/linggen/linggen Website: https://linggen.dev
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