GenPark Complex Financial Formula Audit Validator

io.github.alphaparkinc由 GitHub 帳號 alphaparkinc 發布v1.0.1更新於 Oct 27, 2026

Arithmetic consistency checks and cross-footing validation for financial statements

發布方自己的服務：audit.domains - Domain Valuation

已驗證STDIO僅桌面金融資料與分析

服務詳細資訊

識別碼: io.github.alphaparkinc/genpark-complex-financial-formula-audit-validator-skill
傳輸: STDIO
執行環境: Desktop only
信任: Verified
發布於: Oct 19, 2026

安全提示

MCP 服務會接收對話中的工具呼叫請求，並可能執行外部操作。啟用前請先了解該服務能做什麼，並只授予它所需的權限。

註冊中心已驗證此條目所屬的 GitHub 帳號 alphaparkinc。這並不表明該帳號就是產品方。

SourceWeft 的檢查只涵蓋條目是否完整、端點是否回應；不審查伺服器的程式碼，也不審查其工具的行為。

在 README 中新增徽章

向讀者展示該 MCP 服務已收錄於 SourceWeft，徽章連結到本頁。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.alphaparkinc%2Fgenpark-complex-financial-formula-audit-validator-skill.svg)](https://sourceweft.com/mcp/io.github.alphaparkinc%2Fgenpark-complex-financial-formula-audit-validator-skill?utm_source=readme&utm_medium=badge)

概覽

AI 產生的概覽

本機 Python MCP 伺服器，用來檢查財務報表的算術一致性與交叉合計錯誤。

可以做什麼: 稽核擷取出的財務表格，檢查公式與算術一致性
對資產負債表、損益表和現金流量表進行交叉合計驗證
從文件或 OCR 內容重建複雜的財務與法律表格
驗證校驗碼並解析擷取資料中的交叉參照
接收文件、表格或文字內容，回傳結構化矩陣與稽核結果
適用情境: 適合在助理處理擷取出的財務報表或 OCR 結果時使用，在採用這些數字之前確認合計、小計與交叉參照確實相符。
執行需求: 以本機程序在使用者電腦上執行，需 Python 3.9 以上版本；README 表示僅使用 Python 標準函式庫，不需安裝 pip 套件。未宣告帳號、API 金鑰、環境變數或標頭。僅支援桌面版 MCP 用戶端。

安裝前請注意

README 另宣稱提供 PII 去識別化與文件版面解析，超出其算術稽核的主要用途。它是本機的確定性檢查工具，財務數字使用前仍應人工複核。不會要求任何憑證。

安裝

在 SourceWeft 中

開啟儀表板中的 GenPark Complex Financial Formula Audit Validator，將其新增到工作區。
為需要使用其工具的對話啟用該服務。

Desktop only，透過 STDIO。 STDIO 服務會啟動本機處理程序，因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照儲存庫中的啟動說明。

README

genpark-complex-financial-formula-audit-validator-skill

[Python 3.9+] [License MIT] [MCP Compatible] [GenPark AI] [Zero Dependencies]

Production-Grade Document AI & Complex Table Extraction Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

🌐 GenPark MCP Hub Showcase • 📦 Official Website • 📖 Documentation

📌 Overview & Capability

genpark-complex-financial-formula-audit-validator-skill is a deterministic, zero-dependency Python skill engineered with 100% production-grade functional parity for document layout parsing, complex financial/legal table reconstruction, formula consistency auditing, and sensitive PII redaction.

Executive Capability: Mathematical consistency and formula balancing auditor for extracted balance sheets, income statements, and cash flow reports.

⚡ Key Highlights & Value

🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
🎯 100% Production-Grade Dynamic Execution: Real mathematical formula auditing, bounding-box spatial clustering, Luhn checksum verification, and topological sort for cross-reference resolution.
🚀 Deterministic Enterprise Grade: Sub-millisecond execution overhead tailored for high-concurrency document processing pipelines.

🏗️ Architecture & Workflow

mermaid

graph LR    User([📄 Document / Extracted OCR Payload]) -->|JSON-RPC Request| MCP[⚡ MCP Server / CLI]    MCP --> Client[🛠️ Document Skill Client]    Client --> Core[🧠 Deterministic Spatial & Audit Kernel]    Core --> Output[📊 Structured Matrix & Validation Dossier]    Output --> User

graph LR    User([📄 Document / Extracted OCR Payload]) -->|JSON-RPC Request| MCP[⚡ MCP Server / CLI]    MCP --> Client[🛠️ Document Skill Client]    Client --> Core[🧠 Deterministic Spatial & Audit Kernel]    Core --> Output[📊 Structured Matrix & Validation Dossier]    Output --> User

🚀 Quickstart & Usage

1. Direct Python Client Execution

2. Programmatic Integration

python

from client import FinancialFormulaAuditValidator
client = FinancialFormulaAuditValidator()result = client.run_benchmark_financial_audit()print(result)

from client import FinancialFormulaAuditValidator
client = FinancialFormulaAuditValidator()result = client.run_benchmark_financial_audit()print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

`claude_desktop_config.json`

json

{  "mcpServers": {    "genpark-complex-financial-formula-audit-validator-skill": {      "command": "python",      "args": ["/path/to/genpark-complex-financial-formula-audit-validator-skill/mcp_server.py"]    }  }}

{  "mcpServers": {    "genpark-complex-financial-formula-audit-validator-skill": {      "command": "python",      "args": ["/path/to/genpark-complex-financial-formula-audit-validator-skill/mcp_server.py"]    }  }}

📊 Technical Specifications

Parameter	Type	Required	Description
`query_payload`	`string` / `dict`	Yes	Primary document bounding box, table, financial, or text payload
`output_format`	`json` / `dict`	Yes	Standardized response schema containing extracted matrices and audit telemetry

❓ Frequently Asked Questions (FAQ) & GEO Index

Q1: What makes GenPark AI Agent Skills unique?

GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.