agentladle-mcp-reoi
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agentladle-mcp-reoiRun REOI valuation for AAPL: sales 1000, WACC 10%, terminal growth 3%"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AgentLadle MCP REOI
δΈζ | English
A Model Context Protocol (MCP) server for Residual Operating Income (REOI) Valuation, built with Python and FastMCP.
π Financial Data & Valuation Engine β A professional quantitative analysis tool for Residual Operating Income modeling.
It enables AI assistants (like Claude, Cursor, etc.) to perform multi-stage residual income projections, discounting, and enterprise value bridging analysis via standardized data input interfaces.
Features
1 Professional MCP Tool providing comprehensive financial valuation capabilities.
Standardized REOI Framework, incorporating base period analysis, forecast period discounting, and terminal value estimation.
Multi-stage Profit Forecasting, allowing independent revenue growth rates and operating margins configuration for each year.
Smart Markdown Formatting, returning not only precise valuation figures but also built-in markdown tables for elegant rendering inside LLM clients.
Zero Configuration Installation β Add one line to your MCP client without cloning or manual setup.
Pure Python, cross-platform (Windows / macOS / Linux).
Related MCP server: Financial Modeling Prep MCP Server
Prerequisites
Python 3.10+ β Download Python
uv β Install uv
Tip: After installing uv, restart your terminal and MCP client (e.g., Claude Desktop) to ensure the
uvcommand is recognized.
Quick Start
Add the following to your MCP client configuration (Claude Desktop, Cursor, etc.):
{
"mcpServers": {
"agentladle-mcp-reoi": {
"command": "uvx",
"args": ["agentladle-mcp-reoi"]
}
}
}That's it. uvx automatically downloads the package and its dependencies from PyPI β no cloning, manual installation, or path configuration required.
Alternative: pip install
If you prefer managing the environment yourself:
pip install agentladle-mcp-reoiThen configure:
{
"mcpServers": {
"agentladle-mcp-reoi": {
"command": "agentladle-mcp-reoi"
}
}
}Alternative: Run from Source (Local Dev)
Clone the repository and run directly:
git clone https://github.com/agentladle/mcp-reoi.gitConfigure your MCP client:
{
"mcpServers": {
"agentladle-mcp-reoi": {
"command": "uv",
"args": ["run", "--directory", "/path/to/mcp-reoi", "agentladle-mcp-reoi"]
}
}
}Replace /path/to/mcp-reoi with the actual path to the cloned repository.
Tool List
# | Tool | Description |
1 |
| Residual Operating Income valuation model. Outputs value per share and detailed breakdown based on financial statements and assumptions. |
Tool 1: reoi_valuation_model
Calculates enterprise equity value and suggested value per share by taking base period financial data and future forecast assumptions.
Parameter List (request object)
Parameter | Type | Required | Description |
| string | Version, default "1.0" | |
| string | Stock ticker | |
| string | Company Name | |
| string | Currency, default "CNY" | |
| object | β | Base period financial data |
| object | β | Valuation parameters |
| object | Optional market consensus data | |
| object | Optional forecast assumptions |
baseData object
Parameter | Type | Required | Description |
| float | β | Total Assets (millions) |
| float | β | Financial Assets (millions) |
| float | β | Total Liabilities (millions) |
| float | β | Financial Liabilities (millions) |
| float | β | Preferred Stock Value (millions) |
| float | β | Minority Equity (millions) |
| float | β | Base Period Sales (millions), must be > 0 |
| float | Base Period Operating Profit (millions) | |
| float | Base Period Core Profit (millions) | |
| float | Base Period Sales Growth Rate | |
| float | Base Period Operating Margin | |
| float | β | Total Shares Outstanding (millions), must be > 0 |
parameters object
Parameter | Type | Required | Description |
| int | Number of Forecast Years (default: 5) | |
| float | β | Discount Rate/WACC, e.g., 0.10 for 10% |
| float | β | Terminal Growth Rate, e.g., 0.03 for 3% |
marketConsensus object (Optional)
Parameter | Type | Required | Description |
| float[] | Array of annual revenue consensus | |
| float[] | Array of annual EPS consensus |
assumptions object (Optional)
Parameter | Type | Required | Description |
| float[] | Array of annual revenue growth rates | |
| float[] | Array of annual operating margins |
Data Flow
Model Input (Financials & Assumptions)
β
βΌ
Input Validation
β
βββ 1. Derive Base Net Operating Assets (NOA) and Asset Turnover
β
βββ 2. Forecast Period Projection (Compute sales, OI, ending NOA, residual income)
β
βββ 3. Terminal Value Calculation (Compute terminal value and discount to present)
β
βββ 4. Value Bridging (Core operating value + Financial Assets - Liabilities - Minority Equity)
β
βΌ
Markdown Detailed Output (Value per share, Data Tables)Tech Stack
Component | Choice | Purpose |
MCP Framework |
| MCP server with stdio transport |
Data Validation |
| Strong typing and JSON Schema generation |
Build Tool |
| Project configuration and dependency management |
Testing |
| Unit testing for the core valuation engine |
License
MIT
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Maintenance
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