genpark-financial-audit

Arithmetic consistency checks for supplied financial statement data.

This checks supplied numbers and a simplified income-statement model. It does not extract PDFs, verify source authenticity, check accounting compliance, or provide an audit opinion. Monetary values must use consistent units; tolerance defaults to 0.5 of those units.

Install from the GitHub release

Python 3.9 or newer. The library and stdio MCP server have no runtime dependencies.

python -m pip install https://github.com/Alpha-Park/genpark-complex-financial-formula-audit-validator-skill/releases/download/v1.0.1/genpark_financial_audit-1.0.1-py3-none-any.whl

PyPI publication is pending account setup. The intended PyPI project is genpark-financial-audit; do not assume pip install genpark-financial-audit is available until the project is published.

Python usage

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

MCP stdio configuration

After installing the wheel, configure your MCP client with the installed command:

{
  "mcpServers": {
    "genpark-financial-audit": {
      "command": "genpark-financial-audit",
      "args": []
    }
  }
}

If the command is not on PATH, use its absolute path or python -m genpark_financial_audit with the same interpreter where you installed the wheel. The GitHub release also contains a .mcpb bundle for clients supporting desktop extensions. That bundle requires a Python 3.9+ interpreter on PATH; it bundles the server source.

Available tools: audit_balance_sheet, audit_income_statement, audit_cross_footing, run_benchmark_financial_audit. tools/list returns required arguments and JSON schemas. Each MCP process holds its own state. Benchmark tools use isolated instances.

Development

python -m unittest discover -s tests
python -m pip install mcp
python tests/check_mcp.py
python -m pip install build twine
python -m build
python -m twine check dist/*

python mcp_server.py --test runs the deterministic example; it is not a protocol conformance test. The MCP client check exercises initialize, tools/list, tools/call and ping over stdio.

Distribution

GitHub source and release artifacts are the primary distribution until PyPI is configured. Registry submissions are tracked separately; a manifest is not proof of registry acceptance. See PUBLISHING.md for the repeatable PyPI workflow.

MIT license. Maintained by GenPark.