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by io.github.CSteenkamp
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Token price candles (OHLCV)

get_token_candles
Read-onlyIdempotent

Open/high/low/close price candles and traded volume for a token, newest last, for charts, trend and volatility questions. Prices are per token in ADA (default) or USD; volume is in ADA. Returns compact rows: [time ISO, open, high, low, close, volumeAda, trades].

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "unit": "<unit>"
    },
    "name": "get_token_candles"
  }
}

Input Schema

NameRequiredDescriptionDefault
unitYesToken unit: 56-hex policy id followed by the asset name in hex (no separator). Get it from `search` or `list_tokens`.
limitNoHow many most recent candles to return (1-500, default 100).
quoteNoCurrency of the prices.ADA
allPoolsNotrue aggregates every pool of the token (volume-weighted price, summed volume); false uses its primary pool.
intervalNoCandle width.1h

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description correctly focuses on data semantics: volume is always in ADA even when prices are quoted in USD, and rows are a compact fixed-shape array. This is real added value beyond the annotations, though it says nothing about gaps in the series or latency/freshness.

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?

Three short sentences, front-loaded with the returned data, then units, then row shape. Every clause carries information an agent would otherwise have to guess.

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 and five fully documented parameters, the description steps in to describe the return row layout and unit conventions, which is exactly the missing piece. Nothing needed to call it correctly is absent.

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 100%, so baseline is 3; the description goes beyond it by clarifying that the quote currency applies to prices while volume remains ADA, which the schema's 'Currency of the prices' does not spell out. It adds nothing extra for limit or allPools, but that ground is already covered.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: OHLCV candles plus traded volume for a token, with ordering ('newest last'). It is clearly distinct from price-spot siblings like get_token_prices, but it never names a sibling to make the boundary explicit.

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

Usage Guidelines3/5

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

'For charts, trend and volatility questions' implies when to reach for this tool, which is useful context. However, there is no explicit exclusion (e.g. 'use get_token_prices for a single current price, get_market_history for token-level market history'), so the alternative routing 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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