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sherajdev

Twelve Data MCP Server

by sherajdev

Get OHLC Time Series

twelvedata_get_time_series
Read-onlyIdempotent

Retrieve historical OHLC candlestick data for any trading symbol. Supports multiple timeframes from 1-minute to monthly for chart analysis and backtesting.

Instructions

Get historical OHLC (Open, High, Low, Close) candlestick data.

Perfect for chart analysis, backtesting, and historical price research. Supports multiple timeframes from 1-minute to monthly data.

Args:

  • symbol (string): Trading symbol

  • interval (string): Candle interval - "1min", "5min", "15min", "30min", "1h", "4h", "1day", "1week", "1month"

  • outputsize (number): Number of candles to return (1-5000, default: 30)

  • start_date (string, optional): Start date YYYY-MM-DD

  • end_date (string, optional): End date YYYY-MM-DD

  • response_format ('markdown' | 'json'): Output format

Returns: Array of OHLC candles with datetime, open, high, low, close, and volume (where applicable).

Examples:

  • "Get 1-hour gold candles" -> symbol: "XAU/USD", interval: "1h"

  • "Daily EURUSD last 100 days" -> symbol: "EUR/USD", interval: "1day", outputsize: 100

  • "5-minute BTC data" -> symbol: "BTC/USD", interval: "5min"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesSymbol for time series data
end_dateNoEnd date for historical data (YYYY-MM-DD)
intervalNoCandle interval (1min, 5min, 15min, 30min, 1h, 4h, 1day, 1week)1day
outputsizeNoNumber of data points to return (1-5000, default: 30)
start_dateNoStart date for historical data (YYYY-MM-DD)
response_formatNoOutput format: 'markdown' for human-readable or 'json' for structured datamarkdown
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint. Description adds return structure (OHLC candles with volume) and constraints (outputsize 1-5000). No contradiction.

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?

Well-structured with sections for Args, Returns, and Examples. Front-loaded with purpose. Every sentence adds value, though Args section slightly redundant with schema.

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

Completeness4/5

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

Covers all 6 parameters, output format, and use cases. Given no output schema, the description adequately explains return data. No missing critical information.

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 covers 100% of parameters with descriptions. The description adds examples and context (e.g., 'Trading symbol', '1-hour gold candles') that enhance understanding beyond schema.

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 explicitly states 'Get historical OHLC candlestick data' with a specific verb and resource. It distinguishes from siblings like twelvedata_get_price by focusing on historical multi-timeframe data.

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?

Clearly states use cases: 'chart analysis, backtesting, and historical price research.' Provides examples to guide selection, but does not explicitly state when to avoid or mention alternative tools.

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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