Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Stock Price (as-of date)

get_stock_price

Read-onlyIdempotent

End-of-day closing price for a company AS OF any calendar date. Pass date to get the close on that day; if the date falls on a weekend or market holiday, it resolves backward to the most recent prior trading day's close (the price_date field tells you which day was actually used, and resolved_backward flags when it stepped back). Omit date for the latest available close. Closes are RAW (not split/dividend-adjusted); div_cash and split_factor carry the corporate-action factors for query-time total-return adjustment. This is EOD market data (not a SEC filing fact), so it carries a price_date rather than a fact_id. Coverage follows your plan's tier slice: Pro and Institutional get the full daily series (full = all companies & all archived history, pro = all companies & last 15 years). On the free plans (sample, benchmark) this tool returns the MONTH-END close instead of a daily bar: the close on the last trading day of the latest COMPLETED calendar month on-or-before the requested date (not an average; the month in progress appears once it ends), from the same archive at coarser granularity. The response's granularity field says which series answered the call ('daily' or 'monthly'); a free-plan response's note also spells out the upgrade path to daily bars. What every plan additionally has — the valuation multiples at each fiscal year end via get_financial_ratios (category 'valuation') and get_valuation_metrics, and 1/3/6/12-month momentum plus the 52-week high/low via get_earnings_signals. This archive is licensed market data, NOT EDGAR, so it does NOT share the 1993 EDGAR floor that applies to fundamentals: the earliest bar differs per security and is 1994 or later. A request before a security's first bar returns zero bars on every tier, Institutional included, and is reported as DATA_COVERAGE rather than a plan limit.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No	As-of calendar date (YYYY-MM-DD). Returns the close of the most recent trading day on or before this date — a weekend/holiday resolves to the prior trading close. Omit to get the latest available close.
`ticker`	Yes	Stock ticker symbol, e.g. AAPL, MSFT — or a CIK (SEC identifier), e.g. '0000320193'.

Output Schema

TableJSON Schema

Name	Required	Description
`cik`	Yes
`note`	Yes
`plan`	Yes
`_meta`	Yes	Provenance envelope — data lineage for every MCP response
`close`	Yes
`ticker`	Yes
`currency`	Yes
`div_cash`	Yes
`price_date`	Yes
`granularity`	Yes
`company_name`	Yes
`split_factor`	Yes
`requested_date`	Yes
`resolved_backward`	Yes
`total_return_index`	No
`is_exact_date_match`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 18, 2026

addedOutput schema / properties / granularity

Added value: +{
+  "enum": [
+    "daily",
+    "monthly"
+  ],
+  "type": "string"
+}

addedOutput schema / properties / total_return_index

Added value: +{
+  "type": [
+    "number",
+    "null"
+  ]
+}

changedOutput schema / required

Previous value: -[
-  "_meta",
-  "ticker",
-  "plan",
-  "cik",
-  "company_name",
-  "requested_date",
-  "price_date",
-  "close",
-  "currency",
-  "is_exact_date_match",
-  "resolved_backward",
-  "div_cash",
-  "split_factor",
-  "note"
-]New value: +[
+  "_meta",
+  "ticker",
+  "plan",
+  "cik",
+  "company_name",
+  "requested_date",
+  "price_date",
+  "close",
+  "currency",
+  "is_exact_date_match",
+  "resolved_backward",
+  "div_cash",
+  "split_factor",
+  "granularity",
+  "note"
+]

Changed1 schema field changedSep 18, 2026

changedOutput schema / properties / _meta / properties / fundamentals_as_of / description

Previous value: -"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to."New value: +"ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt in bulk. Use THIS — not `last_updated` — when telling a user how current the cross-sectional fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to. It is a floor for a single filer, not a ceiling: a filer with a live partition receives its filing, facts and ratios intraday (minutes after EDGAR dissemination), so an entity-scoped read may carry a filing newer than this; cross-sectional ranks (factor scores, earnings signals) refresh with the weekly bulk export."

Changed2 schema fields changedSep 11, 2026

changedInput schema / properties / ticker / description

Previous value: -"Stock ticker symbol, e.g. AAPL, MSFT"New value: +"Stock ticker symbol, e.g. AAPL, MSFT — or a CIK (SEC identifier), e.g. '0000320193'."

changedInput schema / properties / ticker / pattern

Previous value: -"^[A-Za-z.\\-]+$"New value: +"^[A-Za-z0-9.\\-]+$"

Changed2 schema fields changedJul 25, 2026

addedOutput schema / properties / _meta / properties / fundamentals_as_of

Added value: +{
+  "description": "ISO timestamp when the FINANCIAL STATEMENTS were last rebuilt. Use THIS — not `last_updated` — when telling a user how current the fundamentals are. The snapshot is republished on every weekday price refresh while the statements are carried forward unchanged, so `last_updated` can be far more recent than the numbers it sits next to.",
+  "type": "string"
+}

addedOutput schema / properties / _meta / properties / price_as_of

Added value: +{
+  "description": "ISO timestamp when the price surfaces were last refreshed.",
+  "type": "string"
+}

Changed2 schema fields changedJul 7, 2026

addedOutput schema / properties / _meta / properties / cost_usd

Added value: +{
+  "additionalProperties": false,
+  "description": "Per-call cost transparency. Omitted for subscription-only tools that have no PAYG-equivalent price.",
+  "properties": {
+    "amount_usd": {
+      "minimum": 0,
+      "type": "number"
+    },
+    "basis": {
+      "description": "payg_charge = real agent-pay charge. payg_rate_card = indicative price, not billed.",
+      "enum": [
+        "payg_charge",
+        "payg_rate_card"
+      ],
+      "type": "string"
+    },
+    "billed": {
+      "description": "true = this amount was actually charged via PAYG for this call. false = indicative PAYG-equivalent value; your plan already covers this call for free.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "amount_usd",
+    "billed",
+    "basis"
+  ],
+  "type": "object"
+}

addedOutput schema / properties / _meta / properties / latency_ms

Added value: +{
+  "description": "Wall-clock milliseconds this tool call took, measured server-side around the handler.",
+  "minimum": 0,
+  "type": "integer"
+}

AddedJun 29, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds substantial behavioral disclosure beyond that: raw (not split/dividend-adjusted) prices, price_date and resolved_backward fields, backward resolution on weekends/holidays, free-plan monthly fallback, and the data coverage error. No contradiction with 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?

The description is long but information-dense, with the core purpose front-loaded. Each sentence adds meaningful caveats (plan tiers, adjustment factors, data lineage, error codes). It could be trimmed slightly without losing critical information, but the structure is logical and scannable.

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?

With an output schema present, the description properly avoids restating return fields. It covers plan-tier differences, upgrade path via the note field, error behavior, data provenance (licensed market data vs EDGAR), and alternatives, making it fully complete for an agent to invoke the tool correctly without needing external context.

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%, with both parameters already fully documented: the date parameter details the backward resolution and omission behavior, and the ticker parameter explains CIK acceptance. The description repeats this information and adds plan-dependent context, but does not introduce new parameter-level semantics beyond the schema, so the baseline of 3 applies.

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 specific verb+resource: 'End-of-day closing price for a company AS OF any calendar date.' It further distinguishes itself from siblings by explicitly naming get_financial_ratios, get_valuation_metrics, and get_earnings_signals for other data types, and by clarifying it is EOD market data rather than SEC filing facts.

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 guidance on when to use alternatives: valuation multiples via get_financial_ratios/get_valuation_metrics and momentum/52-week high-low via get_earnings_signals. It also explains when to omit date, plan-dependent monthly vs daily granularity, and even the DATA_COVERAGE error behavior for out-of-coverage requests.

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

All Valuein — SEC EDGAR Fundamentals & Smart-Money Data tools Inspect

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