A maintained ctags implementation

💡 Full-featured code intelligence and smart autocomplete for Sublime Text

VS Code extension that allows you to record and play back guided tours of codebases, directly within the editor.

Browser based user interface for the Go source code guru

Language-agnostic code navigation CLI powered by tree-sitter

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Local-only Go static analysis engine with a built-in MCP server. Gives AI coding agents deterministic structural awareness: call graphs, impact analysis, symbol search, and more.

Flowable, Activiti, Camunda BPMN engines process editor plugin for IntelliJ. Pure Kotlin (and some Java)

A parallel universal-ctags wrapper for git repository

Guided code exploration for Neovim with definitions, refs, callers, tests, git, and persistent Trails from the current symbol

MCP for semantic code search & navigation that reduces token waste

"Zero setup" & "Blazingly fast" general code file relationship analysis. With Python & Rust. Based on tree-sitter and git analysis. Support skill and ready for AI🤖

GUI of indexed grep in Windows and Linux. A source code indexing tool, near instant code search tool and navigation

Token-efficient navigation substrate for AI coding agents. Index code once and retrieve only the symbols you need.

Code relationship graph visualization plugin of sublime editor

17 MCP query tools for codebase navigation — functions, classes, imports, dependency graphs, change impact. Zero dependencies. 87% token reduction.

AST knowledge graph MCP server for Claude Code — semantic search, call graph traversal, HTTP route tracing, impact analysis. Auto-indexes 10 languages via Tree-sitter.

Universal MCP to LSP bridge - expose Language Server Protocol capabilities as MCP tools for AI agents

Free, MIT alternative to paid Django schema review. Blast radius on every PR, schema drift, N+1 across functions, ER diagrams, MCP server. No DB, no Django boot, no Pro tier.

Agent skill that builds a queryable belief map of a codebase (modules, boundaries, dependencies, entities) via tree-sitter, so AI coding agents scope changes precisely: architecture discovery, blast-radius and impact analysis, boundary and layer-violation checks, and call/data-flow tracing across Python and TypeScript.