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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Price History (date range)

get_price_history
Read-onlyIdempotent

Daily EOD bar series (OHLCV) for a company over a date range. Returns up to 252 trading-day bars oldest-first — one bar per trading day. Each bar carries: open / high / low / close (raw, unadjusted), total_return_index (dividends reinvested and splits neutralized, forward-compounded from an arbitrary base so only RATIOS of it are meaningful — TOTAL RETURN BETWEEN TWO DATES IS tri_b / tri_a - 1; it is PIT-immutable, so a later dividend appends rather than restating), adjusted_close (the vendor's own back-adjusted series — SPARSELY POPULATED, usually null, and retroactively restated on each corporate action so it is NOT PIT-immutable; prefer total_return_index), volume (shares traded), div_cash (ex-dividend cash per share on that date, 0 on non-dividend days), and split_factor (1.0 on non-split days). Never compute a return from raw close — a 4-for-1 split reads as a 75% crash. If total_return_index is null across the returned bars (a tier that has not re-exported since schema 2.29.0), the response note says so and you should compound close with div_cash / split_factor instead. For a company with more than one listing (dual-class, CVR), bars are the requested share class where the data supports it; listing_resolution and multi_listing on the response say which listing you actually received. Omit start_date for the trailing year before end_date. Omit end_date for the latest available close. Coverage follows your plan's tier slice: Pro and Institutional get the full daily bar series (full = all companies & all archived history, pro = all companies & last 15 years). On the free plans (sample, benchmark) this tool returns MONTH-END bars instead of daily ones: the close on the last trading day of each calendar month in range (not an average), COMPLETED months only (the month in progress appears once it ends), unadjusted, from up to 360 months (~30 years) of the same archive at coarser granularity — open/high/low/volume/adjusted_close are null on a monthly bar (nothing intraday to report), and close/total_return_index/div_cash/split_factor are populated. The response's granularity field says which series answered the call ('daily' or 'monthly'), and a monthly response's note 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
NameRequiredDescriptionDefault
limitNoMaximum number of bars to return. Daily plans (Pro, Institutional): 1–252, default 252 ≈ 1 trading year. Free plans (sample, benchmark), which return month-end bars: 1–360, covering up to the full ~30-year monthly archive. When the range contains more bars than `limit`, the most recent `limit` bars within the range are returned.
tickerYesStock ticker symbol, e.g. AAPL, MSFT — or a CIK (SEC identifier), e.g. '0000320193'.
end_dateNoInclusive end of the date range (YYYY-MM-DD). Defaults to today (the latest available close). Weekends and holidays resolve to the last trading close on or before this date.
start_dateNoInclusive start of the date range (YYYY-MM-DD). Bars on or after this date are returned (up to `limit`). Omit to receive the `limit` most-recent bars before end_date.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYes
barsYes
noteYes
planYes
_metaYesProvenance envelope — data lineage for every MCP response
tickerYes
end_dateYes
bar_countYes
start_dateYes
granularityYes
company_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / limit / description
      Previous value: -"Maximum number of bars to return (1–252; default 252 ≈ 1 trading year). When the range contains more bars than `limit`, the most recent `limit` bars within the range are returned."New value: +"Maximum number of bars to return. Daily plans (Pro, Institutional): 1–252, default 252 ≈ 1 trading year. Free plans (sample, benchmark), which return month-end bars: 1–360, covering up to the full ~30-year monthly archive. When the range contains more bars than `limit`, the most recent `limit` bars within the range are returned."
    • changedInput schema / properties / limit / maximum
      Previous value: -252New value: +360
    • addedOutput schema / properties / granularity
      Added value: +{
      +  "enum": [
      +    "daily",
      +    "monthly"
      +  ],
      +  "type": "string"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "_meta",
      -  "ticker",
      -  "plan",
      -  "cik",
      -  "company_name",
      -  "start_date",
      -  "end_date",
      -  "bar_count",
      -  "bars",
      -  "note"
      -]New value: +[
      +  "_meta",
      +  "ticker",
      +  "plan",
      +  "cik",
      +  "company_name",
      +  "start_date",
      +  "end_date",
      +  "bar_count",
      +  "granularity",
      +  "bars",
      +  "note"
      +]
  2. Changed1 schema field changed
    • 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."
  3. Changed2 schema fields changed
    • 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.\\-]+$"New value: +"^[A-Za-z0-9.\\-]+$"
  4. Changed2 schema fields changed
    • addedOutput schema / properties / bars / items / properties / total_return_index
      Added value: +{
      +  "type": [
      +    "number",
      +    "null"
      +  ]
      +}
    • changedOutput schema / properties / bars / items / required
      Previous value: -[
      -  "price_date",
      -  "open",
      -  "high",
      -  "low",
      -  "close",
      -  "adjusted_close",
      -  "volume",
      -  "div_cash",
      -  "split_factor"
      -]New value: +[
      +  "price_date",
      +  "open",
      +  "high",
      +  "low",
      +  "close",
      +  "adjusted_close",
      +  "total_return_index",
      +  "volume",
      +  "div_cash",
      +  "split_factor"
      +]
  5. Changed2 schema fields changed
    • 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"
      +}
  6. Changed2 schema fields changed
    • 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"
      +}
  7. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only convey read-only, idempotent, non-destructive intent, which the description matches. The description adds extensive behavioral context: unadjusted vs. adjusted values, total_return_index being PIT-immutable, adjusted_close being sparsely populated and restated, the warning against computing returns from raw close, free-plan monthly-bar behavior, and DATA_COVERAGE before a security's first bar. This far exceeds what annotations alone provide.

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 opening sentence is concise and front-loaded, and the description is organized into daily-bar semantics, free-plan differences, and archival caveats. It is long, but the complexity of the tool justifies most details; the 'what every plan additionally has' list is somewhat tangential to invoking this tool, making it slightly less tight than ideal.

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 tier-dependent output, subtle financial data semantics, and edge cases, the description is remarkably complete. It covers null total_return_index fallback logic, listing resolution, granularity field, the upgrade path for monthly bars, zero-bar responses before first listing, and the licensing/coverage timeline. An output schema exists as well, so nothing material is missing.

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?

The schema already documents all four parameters with 100% coverage, so the baseline is 3. The description adds practical semantics: omitting start_date returns the trailing year, omitting end_date returns the latest close, and the limit parameter interacts with tier granularity and range ordering. These operational details enrich the schema's parameter 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?

States a specific verb and resource: 'Daily EOD bar series (OHLCV) for a company over a date range.' It clearly separates this from a single latest-price tool and explains the returned series with all its fields. The scope, granularity, and data semantics are unambiguous.

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?

Provides clear context on when to use it: historical OHLCV over a date range, with precise instructions on omitting start_date or end_date and tier-dependent behavior. It names alternative tools for valuation multiples and momentum (get_financial_ratios, get_valuation_metrics, get_earnings_signals), but it does not explicitly contrast itself with get_stock_price, a closely related sibling.

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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