WACCY
Intelligent financial modelling for small businesses — built in Rust.
Extracts, maps, and synthesises financial data from QuickBooks Online and SEC EDGAR into institutional-quality three-statement models.
Install
# Homebrew (recommended)
brew tap DecisionNerd/tap && brew install waccy
# Cargo
cargo install --git https://github.com/DecisionNerd/waccy
# Python (query-only)
pip install waccy
# Claude Code / Cursor skills
npx skills add DecisionNerd/waccy
# Universal script (also registers MCP server)
curl -fsSL https://raw.githubusercontent.com/DecisionNerd/waccy/main/scripts/install.sh | bash
Quick start
# Extract financial data
waccy extract quickbooks
waccy extract edgar --option cik=0001234567
# Build three-statement model
waccy model
# Query results
waccy query "SELECT * FROM records WHERE statement_kind = 'income_statement'"
MCP server
Register the MCP server (waccy-mcp) with your AI client:
# Claude Code
claude mcp add waccy $(which waccy-mcp)
Then ask your AI agent: "Build a three-statement model from my QuickBooks data."
Distribution surfaces
| Surface | Package | How |
|---|---|---|
| CLI | waccy binary |
Homebrew / cargo install |
| MCP server | waccy-mcp binary |
Registered via claude mcp add |
| Python | waccy on PyPI |
pip install waccy |
| Agent skills | 11 skills | npx skills add DecisionNerd/waccy |
Architecture
crates/
waccy-core/ # Shared library: models, extraction, classification, modeling, query
waccy-cli/ # Binary: waccy CLI
waccy-mcp/ # Binary: waccy-mcp MCP server (JSON-RPC 2.0 over stdio)
waccy-python/ # PyO3 cdylib: Python bindings (built with maturin)
legacy/ # Original Python implementation (archived)
Development
cargo build --release # Build binaries
cargo test --all # Run tests
cargo clippy --all-targets # Lint
cargo fmt # Format
# Python wheel
cd crates/waccy-python && maturin develop
# Full setup
just setup
License
MIT