Valuation Skills MCP Server

io.github.simonmak-ascentv0.1.1Updated Oct 3, 2026

Valuation MCP: DCF/NAV/CCA, cost of capital, derivatives, credit risk, report review.

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Overview

AI-generated overview

A local MCP server that lets an assistant run financial valuations such as DCF, NAV and CCA, price derivatives, and review valuation models and reports.

What it does
It exposes valuation tools covering DCF, NAV and CCA methods, cost-of-capital calculations including Fama-French 5-Factor and WACC, the KMV credit risk model, and derivatives pricing for options, swaps and convertible bonds. It also reviews Excel models and analyses PDF, Word and image documents, and serves a machine-readable method catalog as a resource. It delegates startup-valuation and intangible-valuation tool families, so it is a superset of both.
When to use it
Worth adding when an assistant needs to produce or check fair-value work: running a DCF or NAV valuation on a ticker, computing cost of equity or WACC, pricing derivatives, estimating credit risk, or reviewing an existing Excel valuation model against standards.
Requirements
Runs locally as a stdio process, launched with uvx from the fair-value[mcp] package or installed via pip. Needs Python 3.8+ and dependencies including yfinance, pandas, numpy, scipy, QuantLib-Python, openpyxl, pdfplumber and python-docx. No accounts, API keys or environment variables are declared; market data comes from yfinance over the network.
Before you install
It reads local files when reviewing Excel, PDF, Word or image documents, so point it only at directories you intend to expose. Market data is fetched from yfinance, a third-party service. Outputs are analytical estimates for valuation work, not investment advice, and should be checked before being relied on.

Installation

In SourceWeft

  1. Open Valuation Skills MCP Server 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

Fair Value

[PyPI] [CI] [License: MIT] [MCP Registry]

Professional financial valuation system for OpenCode with IFRS/IVS compliance.

mcp-name: io.github.simonmak-ascent/fair-value

Overview

This project provides comprehensive financial valuation capabilities including:

  • DCF, NAV, and CCA valuations
  • Fama-French 5-Factor cost of equity
  • KMV credit risk model
  • Derivatives pricing (Options, Swaps, CB)
  • Excel model review and validation
  • PDF/Word/Image document analysis

Installation

bash
pip install -r requirements.txt   # dev workflow (unchanged)# or, as a package:pip install .                     # base librarypip install ".[mcp]"              # + MCP server dependencies (A-004)

The console command fair-value-mcp runs the MCP server (stdio; add --http for Streamable HTTP).

MCP Server

bash
# run locally without installing (stdio)uvx --from "fair-value[mcp]" fair-value-mcp
# or install and runpip install "fair-value[mcp]"fair-value-mcp            # stdiofair-value-mcp --http     # Streamable HTTP

The server exposes the native valuation, cost-of-capital, derivatives, credit-risk, and report-review tools, and delegates the startup-valuation and intangible-valuation tool families, so it is a strict superset of both.

Adoption target: ≥ 100 PyPI downloads and ≥ 1 directory listing within 90 days of the first release (tracked via the PyPI stats API and the directory listing).

Quick Start

python
from valuation_engine import run_valuation, review_report, scan_directory
# Run DCF valuationresult = run_valuation('9988.HK', 'dcf')
# Review Excel modelreview = review_report('/path/to/model.xlsx')
# Scan for valuation filesfiles = scan_directory('/path/to/reports/')

Module Structure

src/├── constants.py           # Standards references├── fetch_data.py          # Data fetching (yfinance)├── valuation/             # DCF, NAV, CCA├── cost_of_capital/       # WACC, FF5, KMV├── credit_risk/           # ECL calculations├── derivatives/            # Options, Swaps, CB├── report_review/          # Excel, PDF, Word, Image analysis└── output/                # Report formatting

Requirements

  • Python 3.8+
  • yfinance
  • pandas, numpy, scipy
  • QuantLib-Python
  • openpyxl
  • pdfplumber
  • python-docx

Documentation

See SKILL.md for the capability spec; the machine-readable method catalog is served by the MCP server at the valuation://methods resource, and a docs site is configured via mkdocs.yml.

Standards Compliance

  • IVS 2025
  • IFRS 13 (Fair Value Measurement)
  • IAS 36 (Impairment)
  • HKFRS 9 (ECL)

License

Released under the MIT License.

Source: README.md at commit 1f9d1bf

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Version history

1
  1. v0.1.1LatestOct 3, 2026