Skip to main content
Glama

whale-insights

by com.cryptowhaleinsights

market_context

Get aggregated market context for a date in one call — Fear & Greed, whale summary, sentiment, stablecoin flows, funding rates, golden alerts, analyst summaries (8 sources parallel) — Single-call aggregated market snapshot for a given date. Queries 8 data sources in parallel — Fear & Greed, whale daily summary, social sentiment (BTC/ETH/SOL), stablecoin flows, BTC funding rates, Golden Alerts daily count, analyst daily summaries (shortSummary only), and top arbitrage opportunities. No authentication required. Use ?date=YYYY-MM-DD (default = today; max 730 days back / 2 years). For dates older than 365 days where daily snapshots have been purged, the endpoint automatically falls back to the permanent monthly archive tables, returning monthly averages instead of daily values. metadata.resolution indicates 'daily' (exact day data) or 'monthly' (monthly averages from archive). metadata.dataCompleteness is the percentage of the 8 sources that have data for the requested date (0-100%). Today is cached 5 minutes; hi

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate to retrieve (YYYY-MM-DD). Defaults to today. Max 730 days back (2 years). Dates older than 365d automatically use monthly archive.

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description must disclose behavior. It explains the fallback from daily to monthly archives for old dates, metadata fields like resolution and dataCompleteness, and caching for today. This adds significant behavioral context beyond the schema.

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 somewhat detailed but front-loads the core purpose. It efficiently conveys key points without excessive verbosity, though some minor redundancy exists (e.g., repeating 'single-call aggregated market snapshot').

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 absence of an output schema, the description covers important return metadata (resolution, dataCompleteness) and caching behavior. For a tool with one optional parameter and a clear aggregation function, this is sufficiently complete.

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?

The single parameter 'date' is fully described in the schema. The description adds value by clarifying default (today), maximum range (730 days), and automatic fallback to monthly data. This enhances understanding beyond the schema description.

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 provides an aggregated market snapshot with explicit components (Fear & Greed, whale summary, etc.). It distinguishes itself from sibling tools that are individual endpoints by offering a single-call parallel query of 8 sources.

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 explains the tool is for getting aggregated market context in one call, with details on default date, maximum range (730 days), and fallback behavior for older dates. It does not explicitly state when to use alternatives, but the context is sufficient for an AI agent to understand its primary use.

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

All whale-insights toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but there are a few pairs with overlapping boundaries (e.g., analysts_signals vs analysts_signals_all, whale_movements vs whale_movements_summary) that could cause minor confusion.

Naming Consistency4/5

Naming is predominantly snake_case and descriptive, with minor inconsistencies in plural/singular forms (e.g., 'analysts' vs 'analyst_archive'). Overall pattern is stable.

Tool Count2/5

With 55 tools, the server is quite heavy. While the scope is broad, many tools are history/monthly variants that could be combined, making the count feel inflated beyond what is ideal for a single server.

Completeness4/5

The tool set covers a wide range of crypto analytics domains (analysts, arbitrage, funding, whales, sentiment, etc.). Minor gaps exist (e.g., no direct token price endpoint), but overall it's a comprehensive surface.

Resources