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Show HN: Basic Memory – Build a knowledge graph from Claude conversations

4 点作者 phernandez大约 2 个月前
Basic Memory is an open-source tool that enables Claude to build and navigate a persistent knowledge graph based on your conversations. It solves the problem of lost context in AI interactions by storing knowledge in standard Markdown files on your computer.<p>I built this because I found myself constantly repeating information to LLMs and wanted a system where my knowledge grew naturally through conversations while maintaining complete control over my data.<p>Demo video: <a href="https:&#x2F;&#x2F;basicmachines.co&#x2F;images&#x2F;Claude-Obsidian-Demo.mp4" rel="nofollow">https:&#x2F;&#x2F;basicmachines.co&#x2F;images&#x2F;Claude-Obsidian-Demo.mp4</a><p>Key features:<p>- Continue conversations exactly where you left off without repetition<p>- All knowledge stays in local Markdown files you can edit anytime<p>- Works with Claude Desktop via the Model Context Protocol<p>- Seamless integration with Obsidian for visualization and editing<p>- Fully open source (AGPL)<p>The system works by creating structure from simple markdown patterns:<p>- Observations with categories: `- [category] fact #tag`<p>- Relations between documents: `- relation_type [[WikiLink]]` or plain `[[Wikilinks]]`<p>- These patterns emerge naturally during conversations<p>When you chat with Claude, you can simply say &quot;Let&#x27;s continue our conversation about X&quot; and it will build context from your knowledge base, without needing to upload files every time.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;basicmachines-co&#x2F;basic-memory" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;basicmachines-co&#x2F;basic-memory</a><p>Docs: <a href="https:&#x2F;&#x2F;memory.basicmachines.co&#x2F;" rel="nofollow">https:&#x2F;&#x2F;memory.basicmachines.co&#x2F;</a><p>Website: <a href="https:&#x2F;&#x2F;basicmachines.co&#x2F;" rel="nofollow">https:&#x2F;&#x2F;basicmachines.co&#x2F;</a><p>Requires Claude Desktop or other MCP host and Python 3.12+<p>I&#x27;d love feedback from the HN community, particularly from those interested in knowledge management or AI applications.

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