FinancialMD

Segment data as reported

segments

Read-onlyIdempotent

Return a company's segment facts as the filer tagged them (business segments, geographies, products) from the SEC Financial Statement Data Sets: tag, member, dims and value with the filing as proof. Members are never renamed or mapped across companies; eliminations appear under dims.ConsolidationItems. tag narrows to one line (for example RevenueFromContractWithCustomerExcludingAssessedTax). Filing-layer read: served with generous limits on every tier. Use it when asked for revenue or profit by business line, geography or product. If a dataset, field, company or analysis you need is missing, call request_data.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tag": "RevenueFromContractWithCustomerExcludingAssessedTax",
      "kind": "geography",
      "company": "ticker:AAPL"
    },
    "name": "segments"
  }
}

Input Schema

Name	Required	Description	Default
`tag`	No	Only this XBRL tag.
`kind`	No	Segment axis kind.
`as_of`	No	Knowledge date or timestamp (YYYY-MM-DD or RFC 3339). The answer is what FinancialMD knew at that instant: only facts whose known interval contains as_of. Omit for the current view.
`limit`	No	Maximum number of periods or items to return (default 2, at most 20).
`company`	Yes	Company identifier: a FinancialMD id ("fmd_01H..."), an SEC CIK ("cik:320193"), or a ticker ("ticker:AAPL", optionally with the MIC "ticker:AAPL.XNAS"). A bare ticker like "AAPL" is accepted and sent as ticker:AAPL.
`period_type`	No	Annual (four-quarter) or quarterly facts.	annual

Output Schema

Name	Required	Description
`data`	No	{ period_type, items: [{ tag, taxonomy, kind, member, dims, period_end, value }], note }
`meta`	No	Request metadata: request_id, as_of, company resolution, coverage, pipeline_version, licence, terms, proof_base.
`error`	No	Present only on isError results: the API error code and message plus remedy hints.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds substantive context beyond them: members are never renamed or mapped across companies, eliminations surface under dims.ConsolidationItems, and it is a filing-layer read available on every tier. Those are exactly the data-shape and availability facts an agent cannot get from annotations.

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?

Front-loaded with the core purpose, then caveats, then the fallback routing — a sensible order with little filler. The sentence about generous limits on every tier is closer to a tier guarantee than to tool behavior, but it is short and does inform availability.

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?

For a 6-parameter read tool with a full output schema and complete annotation coverage, the description supplies source provenance, output shape hints (dims.ConsolidationItems), an invariance guarantee across filers, and an escalation path. Nothing an agent needs to call it correctly appears to be missing.

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

Parameters3/5

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

Schema description coverage is 100% and the schema already documents company formats, as_of knowledge-date semantics, limit bounds and the two enums. The description's only parameter-level contribution is that 'tag narrows to one line,' but the example tag it cites is already present in the schema's object-level examples, so it adds little beyond structured data.

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?

States a specific verb and resource ('Return a company's segment facts'), enumerates the covered segment types (business, geographies, products), and names the source (SEC Financial Statement Data Sets). The phrase 'as the filer tagged them' plus the 'never renamed or mapped' caveat clearly separates it from the standardized siblings.

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

Usage Guidelines4/5

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

Gives an explicit use case ('when asked for revenue or profit by business line, geography or product') and routes missing data to the request_data sibling. It does not explicitly contrast with financials_as_reported or filing_facts for the total-company case, so the boundary with the closest siblings is left to inference.

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

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