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ScrapeMole Quotes

ScrapeMole Quotes: stock, ETF, index, FX and crypto market data for AI agents: OHLCV price history

history
Read-onlyIdempotent

Use for charts, backtests, returns and volatility: returns open/high/low/close/adjusted close/volume bars for one ticker over a range (1d, 5d, 1mo, 3mo, 6mo, ytd, 1y, 2y, 5y, 10y, max) at an interval (5m, 15m, 30m, 1h, 1d, 1wk, 1mo; intraday 5m-30m only up to 1mo, 1h up to 2y). Also returns period return %, high/low and dividends/splits in the range. Default interval depends on range. Up to "limit" most recent bars. Paid tool: x402 USDC on Base, $0.002 per successful call; call without payment to receive the PaymentRequired object.

Input Schema

NameRequiredDescriptionDefault
limitNoMax bars, most recent kept (1-2000).500
rangeNoLookback range.1mo
symbolYesYahoo-style ticker.
intervalNoBar size; default depends on range (1d->5m, 5d->30m, 1mo-1y->1d, 2y/5y->1wk, 10y/max->1mo).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/openWorld annotations, it discloses interval-range validity constraints, that the default interval depends on range, that dividends/splits and period return % are included, and the full payment model (x402 USDC on Base, $0.002 per successful call, unpaid call returns PaymentRequired). This is rich, non-obvious behavioral context.

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 primary use case and tightly packed with no filler, though it is a single dense paragraph mixing returns, constraints, and billing; a light structural split would improve scanability.

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 no output schema, the description carries the return-shape burden and does so (OHLCV+adj close+volume bars, period return %, high/low, dividends/splits). Validity constraints, defaults, and the payment/auth path are all covered, so an agent has everything needed to call it correctly.

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 coverage is already 100%, but the description adds meaning the schema lacks: the combinatorial constraint that 5m-30m intervals only work up to 1mo and 1h only up to 2y, plus 'limit' keeping the most recent bars. That is genuine added value over the enum/default documentation.

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+resource: returns OHLCV bars (open/high/low/close/adjusted close/volume) for one ticker over a range at an interval. It is clearly distinguishable from siblings like quote/quotes (current price) and crypto_search/search (lookup), so an agent can select it without opening the schema.

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?

Opens with concrete use cases ('charts, backtests, returns and volatility') and gives scoping rules (one ticker, intraday limits). It does not, however, explicitly name an alternative such as quote for a single snapshot or state when-not to use it, so it stops short of full routing guidance.

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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