From source code to intelligent context — every layer explained
Your code flows through these stages to become instant, queryable knowledge
60+ symbol types
30+ languages
14 native grammars
+ 20 regex fallback
Nodes + Edges
PageRank scoring
chokidar
real-time sync
git-aware
symbol-level diffs
SQLite database
10 memory categories
Compression · Progressive Disclosure · Smart Retrieval
Search · Explain · Trace · Remember
Claude · Cursor · Copilot · Windsurf · Zed
Like human memory — working, episodic, and semantic
Current conversation context
Recent session history
Permanent knowledge graph
14 native Tree-Sitter grammars + 20 regex fallback parsers
+ 20 more via regex fallback (YAML, TOML, Markdown, SQL, Lua, Zig, …)
12 edge types capture every code relationship
Function invocations
Module dependencies
Public API surface
Class inheritance
Interface contracts
Variable references
Decorators/annotations
Method overriding
Nested symbols
Test → implementation
External packages
Route → handler
Not all code is equally important. AI Mind Map knows which symbols matter most.
Just like Google ranks web pages by incoming links, AI Mind Map ranks code symbols by how many other symbols reference them.
Edge weights affect ranking: calls (1.0), inherits (0.8), imports (0.5), uses (0.3)