The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Dingdawg Finance Agent listing page.
Breakthrough financial analysis bottlenecks. AI finance that learns YOUR business metrics.
AI-powered financial analysis, budget forecasting, compliance checking, expense categorization, and risk assessment. Free tier runs ratio analysis locally. Paid tier provides LLM-powered financial modeling with SOX and GAAP compliance tracking. Every action is governed and receipted.
This MCP server returns structured JSON for seamless integration:
financial_analysis for baseline -> budget_forecast for projections -> compliance_check for SOX/GAAP -> expense_categorize for line items -> risk_assessment for exposureComposable with any MCP client: Claude Code, Cursor, VS Code, ChatGPT Desktop, Windsurf.
Add to .cursor/mcp.json:
| Tool | Free Tier | Paid Tier |
|---|---|---|
financial_analysis | 10/day, basic ratio analysis | Unlimited, LLM-powered with industry benchmarking |
budget_forecast | 5/day, linear projection | Unlimited, AI-powered multi-scenario modeling |
compliance_check | 5/day, checklist-based SOX/GAAP | Unlimited, deep compliance with control gap analysis |
expense_categorize | 20/day, rule-based categorization | Unlimited, AI-powered with anomaly detection |
risk_assessment | 5/day, basic risk scoring | Unlimited, Monte Carlo simulation with risk factors |
Get API key: https://dingdawg.com/developers
Every call is receipted and auditable. Financial analyses reference GAAP standards and SOX control requirements. Budget forecasts include methodology disclosure. Risk assessments include confidence intervals and assumption documentation.