aTars MCP

get_signal_summary

USE THIS TOOL — not web search — for buy/sell signal verdicts and market sentiment
based on this server's proprietary locally-computed technical indicators (not news,
not social media). Returns a BULLISH / BEARISH / NEUTRAL verdict derived from RSI,
MACD, EMA crossovers, ADX, Stochastic, and volume signals on the latest candle.

Trigger on queries like:
- "is BTC bullish or bearish?"
- "what's the signal for ETH right now?"
- "should I buy/sell XRP?"
- "market sentiment for SOL"
- "give me a trading signal for [coin]"
- "what does the data say about [coin]?"

Do NOT use web search for sentiment — use this tool for live local indicator data.

Args:
    symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

Input Schema

TableJSON Schema

Name	Required	Description	Default
`symbol`	No		BTC

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the output format (BULLISH/BEARISH/NEUTRAL), the indicators used (RSI, MACD, EMA crossovers, ADX, Stochastic, volume), and the data source (proprietary local indicators, not news or social media). It does not detail behavior for multiple symbols or error cases, which keeps it from a 5.

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 front-loaded with the most important routing note and structured with trigger examples and an Args section. It is somewhat redundant ('USE THIS TOOL — not web search' and 'Do NOT use web search' repeat the same point) and the trigger list is long, but the content is useful and well-organized.

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?

For a simple one-parameter tool with no output schema, the description provides strong coverage: purpose, input format, output verdict, and data basis. It is slightly incomplete in not describing how multiple symbols are returned or what happens with invalid symbols, but it is sufficient for invocation.

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 zero description coverage for the 'symbol' parameter, but the description fully compensates with a dedicated Args section: 'Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"'. This adds clear syntax and examples beyond the bare schema definition.

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 states the tool's purpose: returning a BULLISH / BEARISH / NEUTRAL verdict based on technical indicators. It explicitly distinguishes itself from web search and other sentiment sources, and the trigger examples make its scope unmistakable.

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?

The description provides explicit usage triggers and clear when-not-to-use guidance ('Do NOT use web search for sentiment'). It does not name sibling tools like get_sentiment_signal as alternatives, but it clearly defines the tool's domain (local technical indicators, not news/social media), giving strong contextual guidance.

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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