Intangible Asset Valuation Engine
A complete intangible asset valuation library implementing 124+ functions from the Intangible Asset Valuation textbook — Python library, MCP server, and AI-agent skills.
[CI]
[MCP Registry]
[Glama]
[MCP tools]
[PyPI]
[Python 3.11+]
[Coverage]
[Docs]
[OpenSSF Scorecard]
[License: MIT]
Overview
A production-grade Python library for intangible asset valuation, implementing every formula from the Intangible Asset Valuation textbook by Simon Mak, William Yuen, Paul Wu, and Wayne Hu (Valuation in Practice Series, Ascent Partners). Designed for developers, financial analysts, accountants, and AI agents who need auditable, structured valuation computations for ASC 805 / IFRS 3 compliant workflows.
Three-layer architecture:
- Python Library — 22 modules, 124+ typed functions, all returning
ValuationResult (value + assumptions + steps + formula reference)
- MCP Server — 14 folded tools (124+ formulas) for AI agents via stdio and hosted Streamable HTTP
- AI-agent skills — 4 skill definitions with workflow guidance for valuation domains
Installation
Quick Start (≤ 5 minutes)
Fastest path: no install — point an MCP client at the hosted endpoint
https://intangible-valuation.ascent-partners.com/api/mcp (Streamable HTTP); or one line locally:
pip install "intangible-valuation[mcp]".
Python Library
MCP Server (for AI Agents)
The server exposes 14 tools, each folding a family of formulas behind a
method argument — time value, discount rates, cost/market/income approaches,
IP, technology, customer and human-capital assets, goodwill and purchase price
allocation, impairment, royalty analysis, uncertainty (Monte Carlo / decision
trees), and transfer-pricing / litigation.
Local (stdio):
Hosted (Streamable HTTP) — no install, no API key:
OpenCode — add to opencode.json:
Claude Desktop / Cursor — add the HTTP URL
https://intangible-valuation.ascent-partners.com/api/mcp as an MCP server, or run the
stdio entrypoint above.
MCP Registry & Glama — published as
com.ascent-partners/intangible-valuation. The
server.json manifest declares both the hosted
streamable-http remote and a PyPI stdio package, and
glama.json carries the Glama listing. Install and run the stdio
server from either registry:
Listed on
Glama and
the Official MCP Registry.
Prompts and resources. Besides the 14 tools, the server offers three guided
prompts (purchase_price_allocation, value_ip_asset, impairment_test) and a
machine-readable method catalog at intangible-valuation://methods, so agents can
see every method's required parameters before calling a tool.
AI-agent skills
Copy the skills/ directory to your agent's skills folder:
asset-valuation — Patents, trademarks, technology, customer relationships, human capital
discount-rate-construction — Build-up, CAPM, WACC, risk premiums, adjustments
purchase-price-allocation — ASC 805 / IFRS 3 PPA workflow, goodwill calculation
impairment-testing — ASC 350, IAS 36 goodwill and intangible impairment
Valuation Methods by Category
The three approaches
Distribution
Why This Library?
- Auditable — Every function returns
ValuationResult with value, method, formula reference, assumptions, and step-by-step calculation breakdown
- Textbook-accurate — All 124+ formulas verified against book example values with 1056 unit tests
- AI-ready — MCP server (14 folded tools) and Skills for seamless AI agent integration
- Complete coverage — All three valuation approaches (cost, market, income) across 19 chapters
- Open source — MIT license, extensible, well-documented
Development
Note: CI and deployment run through the APG workbench pipeline.
Documentation
Companion Textbook
Intangible Asset Valuation: A Comprehensive Guide to Valuing Brands, IP, Technology, and Human Capital
Theory, Methods, Regulation, and Practice — Valuation in Practice Series by Ascent Partners
By Simon Mak, William Yuen, Paul Wu, Wayne Hu · 176 pages · 19 chapters · 3 appendices
Citing This Project
Based on formulas from the Intangible Asset Valuation textbook.
Use with Context7
Up-to-date Intangible Asset Valuation Engine documentation is indexed on Context7, so coding agents can pull it into context on demand. With the Context7 MCP server or ctx7 CLI installed, name the library in your prompt:
License
MIT — see LICENSE.
By Ascent Partners — part of the Valuation in Practice Series.
If this saves you time, a ⭐ on GitHub helps others find it.