mcp-server

Global market summary

market_summary

Read-onlyIdempotent

One-call summary of total market cap, 24h volume, BTC/ETH dominance, and recent trend.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`trend24h`	No	24h trend as a decimal (0.02 = +2%)
`btcDominance`	Yes	BTC share of total market cap, 0-100
`ethDominance`	Yes	ETH share of total market cap, 0-100
`volume24hUsd`	Yes	Combined 24h trading volume
`totalMarketCapUsd`	Yes	Combined market cap of all tracked coins

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedMay 21, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "btcDominance": {
+      "description": "BTC share of total market cap, 0-100",
+      "type": "number"
+    },
+    "ethDominance": {
+      "description": "ETH share of total market cap, 0-100",
+      "type": "number"
+    },
+    "totalMarketCapUsd": {
+      "description": "Combined market cap of all tracked coins",
+      "type": "number"
+    },
+    "trend24h": {
+      "description": "24h trend as a decimal (0.02 = +2%)",
+      "type": "number"
+    },
+    "volume24hUsd": {
+      "description": "Combined 24h trading volume",
+      "type": "number"
+    }
+  },
+  "required": [
+    "totalMarketCapUsd",
+    "volume24hUsd",
+    "btcDominance",
+    "ethDominance"
+  ],
+  "type": "object"
+}

First observedMay 20, 2026

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description adds marginal value by specifying the exact data returned (market cap, volume, dominance, trend). It does not disclose any additional behavioral traits beyond the annotations.

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?

Single sentence that is front-loaded and concise, containing no superfluous words. Every word contributes to the description.

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?

Given zero parameters, presence of an output schema, and rich annotations, the description fully covers what the tool does and returns. It is complete for the tool's complexity.

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?

No parameters exist, so schema coverage is 100%. Description adds no parameter info but is not needed; baseline of 4 is appropriate for 0-parameter tools.

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 it provides a one-call summary of total market cap, 24h volume, BTC/ETH dominance, and recent trend, using specific verbs and resources. It distinguishes well from sibling tools like get_price or top_coins which are more specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for a quick global overview but does not explicitly state when to use versus alternatives like get_price or top_movers. It lacks when-not-to-use 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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