whale-insights

funding_rates_history

Read-onlyIdempotent

Funding rates history (daily snapshots) — Returns the daily historical perpetual futures funding rate for a single token over the last N days (default 30, max 180). Rates are sourced from Gate.io, MEXC, and Kraken, recorded once per day from the live 5-min funding-rate cycle. Top 10 tokens by volume are snapshotted: BTC, ETH, SOL, BNB, XRP, DOGE, ADA, AVAX, LINK, DOT. Each day includes per-exchange rates (gateio/mexc/kraken) plus a derived avg and sentiment label. Sentiment: avg > 0.05% = bearish (leveraged longs paying shorts → market top signal); avg < -0.01% = bullish (shorts paying longs → market bottom signal); otherwise neutral. Use ?symbol=BTC&days=30 (symbol defaults to BTC; days is 1–180). Cold-start days with no data are omitted. Cached 5min. — Use this for daily historical data; use the corresponding live snapshot tool for current conditions and the monthly tool for long-term trends.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Number of recent days to return (1–180, default 30).
`symbol`	No	Token symbol to look up (BTC, ETH, SOL, BNB, XRP, DOGE, ADA, AVAX, LINK, DOT). Case-insensitive. Defaults to BTC.	BTC

Output Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No
`total`	No
`symbol`	No
`history`	No
`updatedAt`	No
`attribution`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "attribution": {
+      "$ref": "#/components/schemas/Attribution"
+    },
+    "days": {
+      "type": "number"
+    },
+    "history": {
+      "items": {
+        "properties": {
+          "avg": {
+            "description": "Average across available exchanges.",
+            "type": "number"
+          },
+          "date": {
+            "description": "Snapshot date (YYYY-MM-DD, UTC).",
+            "format": "date",
+            "type": "string"
+          },
+          "gateio": {
+            "description": "Gate.io funding rate in % (e.g. 0.01 = 0.01% per 8h). Null when unavailable.",
+            "nullable": true,
+            "type": "number"
+          },
+          "kraken": {
+            "description": "Kraken funding rate in %. Null when unavailable.",
+            "nullable": true,
+            "type": "number"
+          },
+          "mexc": {
+            "description": "MEXC funding rate in %. Null when unavailable.",
+            "nullable": true,
+            "type": "number"
+          },
+          "sentiment": {
+            "description": "Market sentiment derived from avg: >0.05% bearish (top signal), <-0.01% bullish (bottom signal).",
+            "enum": [
+              "bullish",
+              "bearish",
+              "neutral"
+            ],
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "symbol": {
+      "type": "string"
+    },
+    "total": {
+      "type": "number"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedJun 26, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: data sources (Gate.io, MEXC, Kraken), daily snapshot method, cold-start omission, cache duration, and the sentiment-label thresholds. No contradiction with annotations.

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 dense and front-loaded with the core purpose, and nearly every sentence adds useful context. It is somewhat long and repeats default/max information, but the content is relevant and organized in a logical flow from result to semantics to usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return-value documentation is not needed. The description covers token universe, data sources, sampling frequency, derived fields, sentiment meaning, caching, edge cases like cold-start days, and alternative tools, making it complete for an agent deciding to call it.

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?

Schema coverage is high, so the baseline is 3, but the description adds meaningful usage details: case-insensitive symbols, example query, default values, and sentiment threshold interpretation. However, it introduces a discrepancy by saying max 180 while the schema maximum is 90, preventing a perfect score.

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 states a specific verb and resource: returns daily historical perpetual futures funding rates for a single token over N days. It also distinguishes itself from sibling tools by naming the live snapshot tool and monthly tool as covering different time horizons.

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 says 'Use this for daily historical data; use the corresponding live snapshot tool for current conditions and the monthly tool for long-term trends.' It also gives defaults, ranges, and an example query, leaving no doubt about when to invoke this tool.

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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