Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@dingdawg-finance-agent analyze my Q3 financial ratios"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 ratios (liquidity, profitability, solvency) with industry benchmarks
SOX/GAAP compliance status with specific control gap identification
Governance receipt on every call (audit-ready)
Chain-ready: financial_analysis for baseline -> budget_forecast for projections -> compliance_check for SOX/GAAP -> expense_categorize for line items -> risk_assessment for exposure
Composable with any MCP client: Claude Code, Cursor, VS Code, ChatGPT Desktop, Windsurf.
Related MCP server: financeskills
npx dingdawg-finance-agentclaude mcp add finance -- npx dingdawg-finance-agentAdd to .cursor/mcp.json:
{"mcpServers": {"finance": {"command": "npx", "args": ["dingdawg-finance-agent"], "env": {"DINGDAWG_API_KEY": "your-key"}}}}npx dingdawg-setupTool | Free Tier | Paid Tier |
| 10/day, basic ratio analysis | Unlimited, LLM-powered with industry benchmarking |
| 5/day, linear projection | Unlimited, AI-powered multi-scenario modeling |
| 5/day, checklist-based SOX/GAAP | Unlimited, deep compliance with control gap analysis |
| 20/day, rule-based categorization | Unlimited, AI-powered with anomaly detection |
| 5/day, basic risk scoring | Unlimited, Monte Carlo simulation with risk factors |
Free: 10 analyses/day, basic ratios
Pro: $49/mo, 100 calls/day, AI-powered deep analysis
Pay-as-you-go: $0.25/call, no commitment
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.
Generate AI-powered budget forecasts with scenario analysis. Requires DINGDAWG_API_KEY for LLM-powered projections.
Inputs: expense_history (required), revenue_history (required), assumptions, forecast_months.
Check financial compliance against SOX, GAAP, IFRS, or AML regulations. Requires DINGDAWG_API_KEY for LLM-powered analysis.
Inputs: process_description (required), frameworks.
Free AI expense categorization with tax deduction flags. Deep LLM-powered analysis and optimization with API key.
Inputs: expenses (required), tax_year.
Free AI financial ratio analysis. Returns health score, key ratios, and red flags. Deep LLM-powered modeling and recommendations available with API key.
Inputs: cash, assets, revenue, expenses, +2 more.
AI-powered financial risk assessment for portfolios, investments, or business decisions. Requires DINGDAWG_API_KEY.
Inputs: description (required), time_horizon, risk_tolerance.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 5 tools
Each tool targets a distinct financial domain: compliance (regulatory rules), analysis (ratio health), forecasting (budget scenarios), categorization (expense flags), and risk assessment (portfolio/business risk). No two tools overlap in purpose, and their descriptions reinforce clear boundaries.
All tool names follow a consistent noun_verb/verb_noun pattern using snake_case: compliance_check, financial_analysis, budget_forecast, expense_categorize, risk_assessment. The pattern is predictable and consistent, matching the style of well-organized MCP servers.
With 5 tools, the server is well-scoped for a financial agent, covering common user requests without being bloated or minimal. Each tool has a clear role, and the count is squarely within the recommended range for a focused server.
The tool surface covers the major financial workflows an agent might need: compliance verification, ratio analysis, forecasting, expense tracking, and risk assessment. Minor gaps exist, such as no dedicated tool for tax estimation or investment portfolio management, but these are beyond the core scope and agents can typically work around them.
Connect AI agents to financial institution origination, analytics, and compliance workflows.
Authority, mandate, and policy checks for AI finance with replayable evidence. Not live execution.
Financial intelligence for AI: manage balances, transactions, payments, and more
Proof-of-spend and reserve checks for AI agents: receipts, spend audit, NAV, reconciliation.