GenPark Complex Financial Formula Audit Validator

io.github.alphaparkinc由 GitHub 账号 alphaparkinc 发布v1.0.1更新于 Oct 27, 2026

Arithmetic consistency checks and cross-footing validation for financial statements

发布方自己的服务：audit.domains - Domain Valuation

已验证STDIO仅桌面金融数据与分析

服务详情

标识符: io.github.alphaparkinc/genpark-complex-financial-formula-audit-validator-skill
传输: STDIO
运行时: Desktop only
信任: Verified
发布于: Oct 19, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 alphaparkinc。这并不表明该账号就是产品方。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

[![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)

概览

AI 生成的概览

本地 Python MCP 服务器，用于检查财务报表的算术一致性与交叉合计错误。

可以做什么: 审计提取出的财务表格，检查公式与算术一致性
对资产负债表、利润表和现金流量表进行交叉合计校验
从文档或 OCR 载荷中重建复杂的财务与法律表格
校验校验和并解析提取数据中的交叉引用
接收文档、表格或文本载荷，返回结构化矩阵与审计结果
适用场景: 适合在助手处理提取出的财务报表或 OCR 结果时使用，在依赖这些数字之前确认合计、小计与交叉引用确实对得上。
运行要求: 作为本地进程在用户机器上运行，需 Python 3.9 或更高版本；README 称仅使用 Python 标准库，无需安装 pip 包。未声明账号、API 密钥、环境变量或请求头。仅支持桌面 MCP 客户端。

安装前请注意

README 还宣传 PII 脱敏和文档版面解析，超出其算术审计的主要用途。它是本地确定性检查工具，财务数字使用前仍应人工复核。不索取任何凭据。

安装

在 SourceWeft 中

打开控制台中的 GenPark Complex Financial Formula Audit Validator，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照仓库中的启动说明。

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.