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Quick Start

Five minutes from pip install to answering questions about your codebase.


Prerequisite

bash pip install agsuperbrain

See Install for alternatives (uv, from source) and system requirements.


1. Initialize — one command does it all

Inside your project directory:

bash agsuperbrain init

This single command:

  1. Creates .agsuperbrain/ with config.yaml and .agsuperbrainignore
  2. Updates your .gitignore
  3. Runs ingest on your project root — parses your code into a graph (no LLM calls, pure AST). Walks every subdirectory and automatically skips .venv, node_modules, __pycache__, .git, dist, build, and other standard noise. Works identically for flat Python, src-layout Python, Maven/Gradle/Spring Boot, Go, Rust, .NET, Rails, Flutter, Swift, Unity, Unreal, and monorepos.
  4. Runs index-vectors — embeds everything for semantic search (downloads ~80 MB model on first run)
  5. Starts the background watcher — subsequent edits are auto-indexed

By the time init finishes, your graph is live and ready to query.

Overriding the defaults

bash agsuperbrain init --src ./services/api # ingest one workspace (monorepos) agsuperbrain init --skip-ingest # config + watcher only, ingest later

Add custom exclusions (e.g., generated/, vendor/) to .agsuperbrainignore or .gitignore.


2. Wire it into your IDE

Pick the tool you use:

bash agsuperbrain claude-install # Claude Code agsuperbrain cursor-install # Cursor agsuperbrain aider-install # Aider agsuperbrain copilot-install # GitHub Copilot CLI agsuperbrain vscode-install # VS Code Copilot Chat agsuperbrain codex-install # Codex agsuperbrain gemini-install # Gemini CLI

Or wire up all 14 supported tools at once:

bash agsuperbrain install --platform all

Full IDE matrix with uninstall commands →


3. Ask questions

From the CLI

bash agsuperbrain ask "how does the auth flow work?"

Super-Brain returns the answer plus evidence — the exact functions, source files, and line numbers it used.

The --llm flag enables the bundled local LLM (Llama-3.2-1B) for richer phrasing. Without it, you get deterministic evidence directly.

bash agsuperbrain search-vectors "payment processing"

Ranks functions and documents by semantic similarity to your query.

Raw graph queries (power users)

bash agsuperbrain query "MATCH (f:Function)-[:CALLS]->(g:Function) WHERE f.name = 'handle_request' RETURN g.qualified_name"

Any Cypher query your KùzuDB supports.


4. (Optional) Visualize the graph

bash agsuperbrain visualize output/graph.html

Opens an interactive Cytoscape.js graph in your browser. Click nodes to navigate, drag to rearrange, zoom into subsystems.


5. (Optional) Ingest docs and audio

Super-Brain is multimodal:

bash agsuperbrain ingest-doc ./design-docs # PDFs, DOCX, PPTX, MD agsuperbrain ingest-audio ./meetings # MP3, WAV, MP4, or a YouTube URL

All go into the same graph and get linked to related code via keyword overlap. Ask "what meeting decided we'd use Postgres?" and the graph returns the transcript segment plus the PRs that followed.


Where the data lives

Data Path
Graph ./.agsuperbrain/graph/
Vectors ./.agsuperbrain/qdrant/
Config ./.agsuperbrain/config.yaml

Everything is local. Nothing ever leaves your machine. One agsuperbrain clean wipes the lot.


Keeping it fresh

The background watcher started by init picks up file changes automatically. You don't need to re-ingest manually.

If you prefer manual control:

bash agsuperbrain watch ./src # continuous watch in foreground agsuperbrain watch ./src --once # single pass


What next?