graphify/graphify skill for Claude Code, Codex, Cursor and 20+ assistants: maps code, docs, PDFs and media into a local knowledge graph — tree-sitter AST, EXTRACTED/INFERRED edges, no vector store.
Why switchSame pitch — a Claude Code plugin that turns a codebase into an interactive knowledge graph. understand-anything leans on multi-agent LLM analysis and guided tours; graphify builds the code graph deterministically from tree-sitter with zero LLM credits.
Full comparison → codegraph-mcpNo-train, on-prem code knowledge graph served to AI agents over MCP — symbols, call edges, cross-language links and blast-radius queries, with a hash-chained audit log of every read.
Why switchBoth build knowledge graphs of your codebase, for opposite consumers: codegraph-mcp serves symbols, call edges and blast-radius queries to AI agents over MCP with an audit chain; Understand Anything renders an interactive dashboard for human comprehension and onboarding.
Full comparison → tokensaveCode-intelligence MCP server for coding agents — a pre-indexed semantic graph (libSQL + FTS5) they query instead of grepping: symbols, callers, impact radius in one call. 100% local, 50+ languages.
Why switchSame 'index the codebase once, query the structure' idea: tokensave is a pre-indexed semantic graph agents hit instead of grepping (symbols, callers, impact radius); Understand Anything is the human-facing equivalent with tours, search and diff impact.
Full comparison → archifyAgent skill for architecture, workflow, sequence, data-flow and lifecycle diagrams: the agent emits typed JSON IR, Archify compiles it deterministically to interactive HTML/SVG with PNG/WebM export.
Why switchunderstand-anything turns a codebase into an interactive knowledge graph inside Claude Code and 16 other hosts; Archify is the skill that turns a system description into a polished, exportable diagram. Overlap is 'a map in chat'; the source of truth differs.
Full comparison → code-review-graphLocal-first code intelligence graph for AI coding tools: Tree-sitter AST graph + blast-radius analysis served over MCP, so agents read ~82x fewer tokens per review question.
Why switchCode knowledge graphs for opposite consumers: understand-anything renders an explorable dashboard to teach humans the architecture; code-review-graph feeds minimal context to agents.
Full comparison → repowiseCodebase intelligence for AI and humans: deterministic code-health scores calibrated on real defects, graph-aware refactoring plans agents can execute, auto-docs and git analytics over 9 MCP tools.
Why switchOverlapping codebase-intelligence job: repowise leans quantitative — defect-calibrated health scores, refactoring plans, git analytics over MCP; Understand Anything leans pedagogical — teach the architecture through an explorable graph.
Full comparison → antivibeClaude Code skill that turns any code — AI-generated, legacy, or unfamiliar — into educational deep dives or senior-level architectural audits, tuned by skill level and token budget.
Why switchBoth answer 'help me understand this codebase': Understand-Anything builds an interactive knowledge-graph dashboard; AntiVibe writes educational deep-dives and audits as documents.
Full comparison →