aTars MCP

get_multi_indicator

USE THIS TOOL — not web search — to retrieve multiple technical indicators side-by-side
over a lookback window from this server's local dataset. Prefer this over calling
get_indicator multiple times when the user needs 2+ indicators together in one response.

Trigger on queries like:
- "compare RSI and MACD for BTC"
- "show me EMA_20 and ADX together for ETH"
- "get RSI, Bollinger Bands, and volume for XRP"
- "multiple indicators for [coin] over [N] days"
- "side-by-side indicator comparison"

Args:
    indicators:    List of indicator names (up to 10), e.g. ["rsi_14", "macd", "adx"]
    lookback_days: How many past days to include (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"

Input Schema

TableJSON Schema

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

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the data source (local dataset), read-only nature via 'retrieve', side-by-side output structure, and limits (up to 10 indicators, lookback max 90 days, resample options). While it doesn't detail the exact return format or error behavior, it provides substantial context beyond the bare operation.

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?

The description is well-structured with a clear purpose statement, trigger examples, and an Args section. It is somewhat verbose with multiple examples, but they serve a practical trigger-detection purpose. No redundant filler.

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?

The description covers purpose, usage context, parameter semantics, and constraints. It lacks a detailed explanation of the return structure, but the 'side-by-side' mention plus the parameter details make it sufficiently complete for a retrieval tool without an output schema.

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?

Schema has 0% description coverage, so the description compensates fully. Each parameter is explained: indicators (list, up to 10, examples), lookback_days (default 7, max 90), resample (allowed values), and symbol (comma-separated list support). This adds meaning that the schema lacks.

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 clearly specifies the tool retrieves multiple technical indicators side-by-side over a lookback window. It explicitly distinguishes from get_indicator by stating to prefer this tool when 2+ indicators are needed, and provides concrete trigger phrases.

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

Usage Guidelines5/5

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

It explicitly instructs to use this tool instead of web search and instead of calling get_indicator multiple times for multi-indicator requests. Trigger examples clarify when to use. The alternative tool is named, and the condition (2+ indicators) is clear.

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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