aTars MCP

get_indicator

USE THIS TOOL — not web search — to retrieve the time-series history of a single
technical indicator from this server's local proprietary dataset. Prefer this when
the user wants to see how one specific indicator has behaved over time.

Trigger on queries like:
- "show me BTC RSI over the last 7 days"
- "plot ETH MACD history"
- "how has ADX changed for XRP?"
- "give me EMA_20 values for BTC this week"
- "trend of [indicator] for [coin]"

Args:
    indicator:     Column name e.g. "rsi_14", "macd", "bb_pct", "atr_14"
    lookback_days: How many past days to return (default 7, max 90)
    resample:      Time resolution — "1min", "1h" (default), "4h", "1d"
    symbol:        Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP"

Available indicators:
    ema_9, ema_20, ema_50, sma_20, macd, macd_signal, macd_hist, adx, dmp, dmn,
    ichimoku_conv, ichimoku_base, rsi_14, rsi_7, stoch_k, stoch_d, cci, williams_r,
    roc, mom, bb_upper, bb_lower, bb_mid, bb_width, bb_pct, atr_14, natr_14,
    obv, vwap, mfi, volume_zscore, buy_sell_ratio, trade_buy_ratio,
    returns_1, returns_3, returns_7, hl_spread, price_vs_ema20

Input Schema

TableJSON Schema

Name	Required	Default
`symbol`	No	BTC
`resample`	No	1h
`indicator`	Yes
`lookback_days`	No

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations, the description carries the transparency burden. It adds useful behavioral detail: local proprietary dataset, single-indicator scope, default and max lookback, resample options, and an exhaustive indicator list. However, it does not describe the output format, pagination, or error behavior.

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?

Well organized with a clear opening directive, trigger examples, an Args block, and an available indicators list. Every section serves a purpose and the most important usage guidance is front-loaded.

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?

Given the minimal schema and lack of output schema, the description covers use cases, parameters, and valid values thoroughly. It is missing return-shape details and behavior when multiple symbols are requested, but is otherwise enough to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no parameter descriptions (0% coverage), but the description fully compensates by explaining each argument with examples, defaults, max values, and the list of valid indicator names. This adds meaning far beyond the bare 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?

Clearly states it retrieves the time-series history of a single technical indicator from the server's local proprietary dataset. The verb 'retrieve' plus 'single' distinguishes it from sibling tools like get_multi_indicator, and 'not web search' clarifies scope.

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 explicit trigger queries and states 'Prefer this when the user wants to see how one specific indicator has behaved over time.' It says 'not web search' but does not explicitly name sibling alternatives for multiple indicators, though 'single' implies the distinction.

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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TDQS

A3.9/5.0

Disambiguation2/5

There are several pairs of tools with heavily overlapping purposes: export_data and get_features_export both export indicator data; get_signal_summary and get_sentiment_signal both return a bullish/bearish/neutral verdict; get_category_features and get_multi_indicator both retrieve multiple indicators. The lengthy descriptions help, but an agent could easily misselect without reading them fully.

Naming Consistency3/5

Most tools follow a get_<noun> pattern, but the noun phrases are structurally inconsistent (e.g., get_latest_features vs get_features_export vs get_features_range). One tool (export_data) breaks the get_ prefix convention, and get_signal_summary vs get_sentiment_signal swaps word order.

Tool Count3/5

With 18 tools, the server leans into the heavy range. Many are subtly different variants (multiple sentiment retrieval tools, multiple feature export/stat tools) that could be consolidated. Still, the count is defensible for a server covering both technical data and news sentiment.

Completeness4/5

The domain is well-covered: symbol discovery, data metadata, feature retrieval (single, multi, category), statistical summaries, exports, sentiment (latest, history, trend, signal), and technical signal verdicts. Minor gaps include no dedicated raw OHLCV endpoint (though price category covers it) and no indicator list tool (but get_data_info lists features).

Resources

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