Dingdawg Finance Agent

io.github.DingDawg-devPublished by GitHub account DingDawg-devv2.0.4Updated Oct 24, 2026

Financial analysis AI. Forecasting, audit prep, SOX/GAAP compliance. Accuracy compounds with use.

The publisher's own server: Finance Foundation

VerifiedSTDIODesktop onlyFinanceData & Analytics

Overview

AI-generated overview

A local finance analysis MCP server that lets an assistant compute financial ratios, forecast budgets, check SOX/GAAP compliance, categorize expenses and assess

What you can do
Run financial ratio analysis (liquidity, profitability, solvency) with industry benchmarks and return structured JSON results, chained from baseline analysis into budget forecasting, compliance checking, expense categorization and risk assessment. Check SOX/GAAP compliance status and identify specific control gaps. Produce budget forecasts with methodology disclosure, and risk assessments with confidence intervals and documented assumptions. Categorize expense line items, with anomaly detection on the paid tier. Attach a governance receipt to every call for audit purposes.
When to use it
Useful when an assistant needs to work through finance tasks such as ratio analysis, budget projections, compliance checks or expense categorization, and when audit-ready receipts and documented methodology matter. The free tier covers basic local ratio analysis; deeper modeling and compliance work requires a paid key.
Requirements
Runs as a local process via npx, so Node.js is needed. A DINGDAWG_API_KEY environment variable is used for paid tier access; the free tier reportedly runs ratio analysis locally. Network access is implied by the hosted API key and pricing model.
Before you install
The server handles financial data, so consider what figures you send. Paid tiers cost money: Pro is listed at $49/mo and pay-as-you-go at $0.25/call, and the API key is a secret to keep out of shared configs. Compliance and risk outputs are advisory and should be verified against actual accounting standards.

Installation

In SourceWeft

  1. Open Dingdawg Finance Agent in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

dingdawg-finance-agent

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.

For AI Assistants

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.

Install

bash
npx dingdawg-finance-agent

Claude Code

bash
claude mcp add finance -- npx dingdawg-finance-agent

Cursor

Add to .cursor/mcp.json:

json
{"mcpServers": {"finance": {"command": "npx", "args": ["dingdawg-finance-agent"], "env": {"DINGDAWG_API_KEY": "your-key"}}}}

Full Stack (all 13 agents)

bash
npx dingdawg-setup

Tools

ToolFree TierPaid Tier
financial_analysis10/day, basic ratio analysisUnlimited, LLM-powered with industry benchmarking
budget_forecast5/day, linear projectionUnlimited, AI-powered multi-scenario modeling
compliance_check5/day, checklist-based SOX/GAAPUnlimited, deep compliance with control gap analysis
expense_categorize20/day, rule-based categorizationUnlimited, AI-powered with anomaly detection
risk_assessment5/day, basic risk scoringUnlimited, Monte Carlo simulation with risk factors

Pricing

  • 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

Governed

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.

Support

[email protected] | https://dingdawg.com

Source: README.md at commit 2b6f16b

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v2.0.4LatestSep 16, 2026

Score

40% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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