Skip to main content
Glama
iabraham23

Finviz + SEC EDGAR MCP Server

by iabraham23

get_per_share_fundamentals

Fetch historical per-share valuation metrics from SEC XBRL filings, including EPS, book value, revenue, and cash flow per share, to replace paid data services.

Instructions

Get historical per-share fundamentals from SEC XBRL filings. Returns annual series of key valuation inputs computed from actual reported values — replaces paid data services like SimFin.

Metrics returned per year:

  • Diluted Shares Outstanding (weighted average, millions)

  • Book Value per Share (Equity / Diluted Shares)

  • Tangible Book Value per Share ((Equity - Goodwill - Intangibles) / Shares)

  • Revenue per Share

  • Operating Cash Flow per Share

  • Diluted EPS (Net Income / Diluted Shares, split-adjusted)

  • Total Revenue (millions)

  • Operating Cash Flow (millions)

Args: ticker: Stock ticker symbol. periods: Number of annual periods (default 10, max ~10 years of data).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes
periodsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the data source (SEC XBRL filings), the computation approach ('computed from actual reported values'), and a clear limitation ('max ~10 years of data'). This is meaningful behavioral context beyond a generic 'Get data' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a lead purpose sentence, a bulleted metric list, and an args section. The 'replaces paid data services like SimFin' note adds context without bloating the text, and each metric listed is distinct and useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description need not explain return structure. It thoroughly covers purpose, parameters, data source, and limitations, leaving little for an agent to infer before making a correct call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully documents both parameters: 'ticker: Stock ticker symbol' and 'periods: Number of annual periods (default 10, max ~10 years of data).' This completely compensates for the schema's lack of property descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states a specific verb+resource: 'Get historical per-share fundamentals from SEC XBRL filings.' The detailed metric list (Diluted Shares, Book Value per Share, etc.) distinguishes it clearly from sibling tools like get_financial_history or get_stock_fundamentals, which cover broader or different financial metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by focusing on historical per-share fundamentals from SEC XBRL data, and notes it 'replaces paid data services like SimFin,' but it never names sibling tools or states when not to use it. An agent must infer when this is preferred over get_financial_history or get_stock_fundamentals.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.