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funding_rates

Read-onlyIdempotent

Get live perpetual futures funding rates — top tokens across Gate.io, MEXC, Kraken with bullish/bearish sentiment — Perpetual futures funding rates aggregated from Gate.io, MEXC, and Kraken, with a derived sentiment label. 3-min cache; check meta.cacheAgeSeconds for exact age. meta.exchangeCount tells how many exchanges contributed data this cycle (up to 3).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaNoResponse freshness metadata. 3-min cache; check `meta.cacheAgeSeconds` for exact age.
tokensNo
updatedAtNo
attributionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "attribution": {
      +      "$ref": "#/components/schemas/Attribution"
      +    },
      +    "meta": {
      +      "description": "Response freshness metadata. 3-min cache; check `meta.cacheAgeSeconds` for exact age.",
      +      "properties": {
      +        "cacheAgeSeconds": {
      +          "description": "Seconds since the cache was last refreshed.",
      +          "type": "integer"
      +        },
      +        "exchangeCount": {
      +          "description": "Number of exchanges that contributed data this cycle (Gate.io, MEXC, Kraken — max 3).",
      +          "type": "integer"
      +        },
      +        "updatedAt": {
      +          "description": "ISO timestamp when this cache entry was populated.",
      +          "format": "date-time",
      +          "type": "string"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "tokens": {
      +      "items": {
      +        "properties": {
      +          "avg": {
      +            "type": "number"
      +          },
      +          "gateio": {
      +            "type": "number"
      +          },
      +          "kraken": {
      +            "type": "number"
      +          },
      +          "mexc": {
      +            "type": "number"
      +          },
      +          "sentiment": {
      +            "type": "string"
      +          },
      +          "symbol": {
      +            "type": "string"
      +          }
      +        },
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "updatedAt": {
      +      "format": "date-time",
      +      "type": "string"
      +    }
      +  },
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds useful behavior beyond that: the 3-minute cache, the cacheAgeSeconds field for exact freshness, and exchangeCount for judging how many exchanges contributed data this cycle. 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening phrase is front-loaded and the cache/exchangeCount sentences carry valuable operational detail. However, the em-dash clause restates the following sentence: exchange sources and the sentiment label are both mentioned twice, which wastes words.

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 zero-parameter, read-only endpoint with an output schema, the description covers the essentials: what data is returned, from which exchanges, the sentiment label, and how to interpret freshness and exchange coverage. It does not explain sentiment derivation, but that is not required to invoke the tool correctly.

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 tool has zero parameters, so the input schema fully covers the parameter space and the baseline of 4 applies. The description adds no parameter info, but none is needed; it usefully documents output metadata fields instead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Get'), a precise object ('live perpetual futures funding rates'), and names the exchanges and the derived sentiment label. It is distinguishable from sibling history/monthly tools by the word 'live', though it does not explicitly contrast with them.

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 gives clear context: this is for current live funding rates rather than historical data, and the 3-minute cache tells agents not to expect instant updates. However, it never names alternatives like funding_rates_history or funding_rate_monthly, nor states when not to use 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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