FinBridge

Get US Company Financials (SEC XBRL)

get_edgar_financials

Read-only

Normalized annual (10-K) or quarterly (10-Q) financial statements for a US company, from SEC EDGAR XBRL company facts (US-GAAP). Values are raw USD (not scaled); eps_diluted is USD per share.

Not this tool for: Korean statements (get_dart_financials), a KR-vs-US pair on one screen (compare_financials_kr_us), or ranking many companies at once (screen_companies, which reads the stored table and covers KR/US/TW/JP/EU). This tool requests one US company's SEC XBRL company facts through the source adapter; results may be reused from a process-local cache for up to 24 hours. data_as_of.generated_at is response creation time, not source retrieval time. Peer comparisons use separately dated database snapshots.

Args:

company (required): ticker / company name / CIK (e.g. 'AAPL', 'Microsoft', '789019')
freq: 'annual' (default, from 10-K) or 'quarterly' (discrete Q1-Q3 from 10-Qs; Q4 is not reported separately)
periods: how many most-recent periods, 1-12 (default 3)
metrics: optional subset of [revenue, gross_profit, operating_income, net_income, eps_diluted, assets, liabilities, equity, cash_and_equivalents, operating_cash_flow] (default all)
response_format: 'markdown' (default) or 'json'

Returns NormalizedFinancials: {company:{name, id(CIK), ticker}, basis:'US-GAAP (10-K)', periods:[{period:'FY2024', fiscal_year, end, currency:'USD', metrics:{revenue, net_income, ...}}], notes}. periods are most-recent first; fiscal_year = calendar year of the period end date.

Examples:

"Apple's revenue and net income for the last 3 years" -> {company:'AAPL', metrics:['revenue','net_income']}
"MSFT last 4 quarters" -> {company:'MSFT', freq:'quarterly', periods:4}

Use when: you need US-GAAP fundamentals for a US-listed company. Don't use for: Korean companies (get_dart_financials), stock prices, or IFRS 20-F foreign private issuers (not supported).

Errors: unknown company -> use search_edgar_company first; companies without us-gaap XBRL facts (funds, 20-F filers) return an error explaining why.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`freq`	No	'annual' = fiscal years from 10-K filings; 'quarterly' = discrete Q1-Q3 from 10-Q filings	annual
`company`	Yes	US company: ticker (e.g. 'AAPL', 'BRK-B' or 'BRK.B'), company name, or CIK number
`metrics`	No	Optional metric subset. Available: revenue, gross_profit, operating_income, net_income, eps_diluted, assets, liabilities, equity, cash_and_equivalents, operating_cash_flow. Default: all
`periods`	No	Number of most-recent periods (default 3)
`response_format`	No	'markdown' for a table, 'json' for compact machine-readable output	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`basis`	No
`notes`	No
`company`	Yes
`periods`	Yes
`data_as_of`	No
`plan_limit`	No
`peer_comparison`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 7, 2026

addedOutput schema / properties / notes

Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

Changed3 schema fields changedSep 7, 2026

addedOutput schema / properties / data_as_of

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": true,
+      "properties": {},
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}

addedOutput schema / properties / peer_comparison

Added value: +{
+  "anyOf": [
+    {
+      "additionalProperties": true,
+      "properties": {},
+      "type": "object"
+    },
+    {
+      "type": "null"
+    }
+  ]
+}

addedOutput schema / properties / plan_limit

Added value: +{
+  "additionalProperties": true,
+  "properties": {},
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description goes beyond this by disclosing caching behavior ('results may be reused from a process-local cache for up to 24 hours'), the meaning of data_as_of.generated_at (response creation time, not source retrieval time), and the fact that peer comparisons use separately dated snapshots. It also explains the ordering of periods and the special case that Q4 is not reported separately in quarterly mode. All of this adds significant behavioral context that annotations alone do not provide.

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

Conciseness5/5

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

The description is well-structured and front-loaded. It leads with the core purpose, then addresses exclusions, parameter details, return structure, examples, and error handling in a logical order. Every sentence earns its place: no fluff, no repetition. Despite being lengthy, it remains efficient because each piece of information is actionable for an agent.

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 tool's complexity (5 parameters, output schema, multiple sibling tools), the description is remarkably complete. It explains the return structure (NormalizedFinancials with company, basis, periods, notes), specifies that periods are most-recent first and fiscal_year is the calendar year of the period end, and details error scenarios (unknown company -> use search_edgar_company; unsupported filers). With an output schema present, the description needn't fully repeat return values, but it does provide enough context for correct invocation and interpretation.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: it explains that 'quarterly' means discrete Q1-Q3 from 10-Q filings and that Q4 is not reported separately, clarifies that values are raw USD and eps_diluted is per share, and gives concrete examples mapping natural language to parameters ('Apple's revenue and net income for the last 3 years' -> {company:'AAPL', metrics:['revenue','net_income']}). This goes beyond the schema's terse parameter descriptions, earning a 4.

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?

The description opens with a precise statement of what the tool does: 'Normalized annual (10-K) or quarterly (10-Q) financial statements for a US company, from SEC EDGAR XBRL company facts (US-GAAP).' This names the verb (get), the resource (financial statements), the source (SEC EDGAR XBRL), and the geographic scope (US). It also explicitly distinguishes itself from siblings like get_dart_financials, compare_financials_kr_us, and screen_companies, making the purpose unambiguous even without reading schemas.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use and when-not-to-use guidance. It lists specific alternatives ('Not this tool for: Korean statements (get_dart_financials), a KR-vs-US pair on one screen (compare_financials_kr_us), or ranking many companies at once (screen_companies)') and a dedicated 'Use when' / 'Don't use for' section. This leaves no doubt about selection criteria, including the unsupported case of IFRS 20-F filers.

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

All FinBridge tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.