BitTide
Menu
中文 Sign in

ast-parsing

Tag

Cards List
#ast-parsing

@PythonHub: Graphify-Labs / graphify Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge g…

X AI KOLs Timeline ↗ · 2026-07-31 Cached

Graphify is an open-source tool that turns codebases, docs, SQL schemas, configs, and PDFs into a queryable knowledge graph for AI coding assistants like Claude Code, Cursor, Codex, and Gemini CLI, using local deterministic AST parsing with no vector store.

0 favorites 0 likes
#ast-parsing

@austinit: Hey friends! Highly recommend CodeGraph: a tool that turns your entire codebase into a structured knowledge graph! It uses Tree-sitter to accurately parse AST, supports 20+ languages, and can be directly fed to AI agents like Claude/Cursor. Before modifying code, instantly see the impact scope, with incredibly accurate context. In practice, tokens are saved by 16% and tool calls reduced by 58%, all local and super secure. Start with one command: npx @colbymchenry/codegraph. A must-have for heavy AI coding! https://colbymchenry.github.io/codegraph/ Worth a try!

X AI KOLs Timeline ↗ · 2026-06-17 Cached

CodeGraph is a local-first tool that converts codebases into structured knowledge graphs. It uses Tree-sitter to precisely parse ASTs and supports over 20 languages. Through the MCP protocol, it directly feeds AI coding agents like Claude and Cursor, helping quickly analyze code impact scope while reducing token consumption and tool call frequency.

0 favorites 0 likes
#ast-parsing

@Potatoloogs: When using Claude Code, Cursor, Codex to understand large projects, you often encounter a problem: every time you ask a question, it has to re-read files, find clues, and piece together context. Code is in src, docs in docs, design specs, screenshots, papers, videos scattered in other directories. Lots of material, but the relationships haven't been captured...

X AI KOLs Timeline ↗ · 2026-05-25 Cached

Graphify is a software engineering knowledge graph tool for AI coding assistants. It organizes project materials such as code, documents, and images into a queryable relationship graph, helping AI skip the step of repeatedly reading files when understanding large projects.

0 favorites 0 likes
← Back to home

Submit Feedback