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openmm-mcp

get_ohlcv

Get OHLCV (candlestick) data for a trading pair

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results to return (default: 100, max: 500)
symbolYesTrading pair symbol (e.g., BTC/USDT, INDY/USDT)
exchangeYesExchange to query. Supported: mexc, gateio, bitget, kraken
timeframeNoCandlestick timeframe (1m, 5m, 15m, 30m, 1h, 4h, 1d, 1w)1h

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, yet it only states the basic fetch action. It does not mention whether the data is historical, how ordering or pagination behaves, what the response contains, or any rate-limits or safety characteristics, leaving an agent without useful 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.

Conciseness5/5

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

The description is a single, front-loaded sentence with no filler or redundancy. It efficiently states the action and resource, which is an ideal size for this simple data-fetch tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema completely documents all four parameters, including defaults and constraints, and OHLCV has a standard financial meaning, so the description is functionally adequate. However, with no output schema and no behavioral notes, details like candle ordering, whether the current incomplete candle is included, and the exact response structure remain unspecified, making the definition complete only at a minimal level.

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%, so the schema fully documents exchange, symbol, limit, and timeframe; the description adds no additional meaning beyond the schema. The phrase 'trading pair' maps to the symbol parameter but does not deepen understanding of any parameter, so the baseline score of 3 is appropriate.

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?

The description uses a specific verb ('Get') and a specific resource ('OHLCV (candlestick) data') for a trading pair, making the tool's function clear. It implicitly differentiates from siblings like get_ticker or get_trades, but it does not explicitly contrast itself with any alternative, so it falls just short of a top score.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as get_ticker or get_trades, and no mention of use cases, prerequisites, or exclusions. The only implied usage is that an agent should call it when candlestick data is requested, but this is left entirely 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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