Skip to main content
Glama
AlgoVaultLabs

crypto-quant-signal-mcp

scan_trade_calls

Read-only

Get ranked BUY/SELL/HOLD trade calls for top crypto perpetual futures by open interest, with confidence and market regime per call. One scan covers the whole market—read-only, no orders.

Instructions

Returns ranked BUY SELL HOLD trade calls across the top crypto perpetual futures by open interest — one scan for whole-market coverage, each with confidence and market regime. Use this for breadth; use get_trade_call for per-coin depth and reasoning. Read-only: reads live exchange APIs, places no orders.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNNoHow many top perps by open interest to scan, 1 to 100 (default 20).
limitNoMax ranked calls to return, 1 to 100 (default 10). Non-HOLD ranked first.
rankByNoUniverse lens: oi (default) volume gainers losers movers funding_positive funding_negative volatility oi_change (aliases vol gain lose move pfr nfr atr oid). funding_*/volatility/oi_change rank among the most-liquid perps; oi_change = real 24h open-interest %Δ.oi
oiBasisNoOI-delta basis for rankBy=oi_change: notional (default, USD) or contracts (base-coin, price-independent). Ignored by other lenses.notional
exchangeNoCrypto venue (default Binance), e.g. Binance Bybit OKX Bitget Hyperliquid.BINANCE
timeframeNoCandle timeframe, 1m to 1d for the scan. Default 15m intraday.15m
includeHoldsNoInclude HOLD calls after non-HOLD (default false).
minConfidenceNoOptional confidence floor, 0 to 100, applied to non-HOLD trade calls.
oiChangeWindowNoOI-delta window for rankBy=oi_change: 1h, 4h, or 24h (default 24h). Ignored by other lenses.24h
minLiquidityUsdNoOptional USD liquidity floor applied to the scan universe: notional open interest, or 24h volume on venues that expose no bulk OI. Omitted means no floor.
includeReasoningNoEnrich each non-HOLD call with price, the top 2-3 drivers, and one-line reasoning (default false → bare verdict cells). HOLDs stay bare. Same per-call detail as get_trade_call.
Install Server

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'Read-only: reads live exchange APIs, places no orders,' adding external-live-data context beyond the annotations. It also discloses that results come with confidence and market regime. No contradiction; the only missing behavioral detail is latency or rate-limit expectations.

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?

Three tight sentences: the first states the core action and scope, the second routes to the sibling, and the third confirms safety. Every sentence earns its place and the most decision-relevant information 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?

Even without an output schema, the description explains the broad return shape: ranked trade calls with confidence and market regime. Combined with the rich parameter schema and the includeReasoning parameter describing per-call enrichment, the agent has enough context to invoke correctly. A more explicit output-shape example would push this to 5.

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%, and every parameter is documented with defaults, ranges, enums, and domain meaning. The description adds no parameter-specific detail, but the schema carries the full burden. Baseline 3 is appropriate.

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 names a specific verb ('Returns'), a specific resource ('ranked BUY SELL HOLD trade calls across the top crypto perpetual futures by open interest'), and the differentiating scope ('one scan for whole-market coverage'). It clearly distinguishes itself from get_trade_call without requiring the reader to open the schema.

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?

Explicitly states when to use this tool ('Use this for breadth') and names the alternative for a different need ('use get_trade_call for per-coin depth and reasoning'). This gives an agent concrete routing guidance between siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AlgoVaultLabs/crypto-quant-signal-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server