Siftly transforms your Twitter/X bookmarks from a chaotic pile of saved tweets into a searchable, AI-categorized knowledge base with an interactive visual mindmap. With over 2,700 GitHub stars since March 2026, the platform runs a four-stage enrichment pipeline on each bookmark: entity extraction mines hashtags, URLs, @mentions, and 100+ known tool domains without API calls; vision analysis generates 30-40 visual tags per image using the Anthropic SDK; semantic tagging produces 25-35 searchable descriptors; and categorization assigns one to three categories with confidence scores. Search combines SQLite FTS5 full-text indexing with Claude-based semantic reranking, narrowing candidates through keyword matching, category-intent detection, and deduplication before sending a bounded set for LLM relevance scoring, letting you find bookmarks by meaning rather than exact keywords. The interactive mindmap built on @xyflow/react renders your entire collection as a force-directed graph organized by category with expandable nodes, color-coded legends, and direct links to original tweets. Import bookmarks through a built-in bookmarklet or console script without browser extensions, then browse in grid or list view with filters for category, media type, and date range. Export as CSV, JSON, or category-grouped ZIP archives. Prisma 7 manages the local SQLite database with FTS5 built in, requiring zero external database setup. A bundled CLI provides JSON-output commands for stats, search, and category management. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.