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forgequant

CoinGlass MCP Server

by forgequant

CoinGlass On-Chain

coinglass_onchain
Read-onlyIdempotent

Analyze cryptocurrency exchange on-chain data to identify market trends, including exchange holdings, balance changes, and transaction flows for assets like BTC and ETH.

Instructions

Get on-chain exchange data.

Track exchange holdings and flows:

  • Increasing exchange balance: Potential selling pressure

  • Decreasing exchange balance: Accumulation (bullish)

Examples: - All exchange holdings: action="assets" - BTC balances: action="balance_list", asset="BTC" - Balance history: action="balance_chart", asset="BTC", exchange="Binance"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesassets: exchange holdings | balance_list: balances by asset | balance_chart: historical | transfers: ERC-20 transactions
exchangeNoExchange filter
assetNoAsset: BTC, ETH, USDT
rangeNoTime range: 7d, 30d, 90d
transfer_typeNoFilter transfers by type
limitNoNumber of records

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, so the agent knows this is a safe, read-only operation. The description adds useful context about interpreting exchange balance trends (bullish/bearish implications), which goes beyond the annotations. However, it doesn't mention rate limits, authentication needs, or data freshness.

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?

The description is efficiently structured: a clear purpose statement, bullet points explaining what to track, and specific examples. Every sentence earns its place by providing either conceptual context or practical usage guidance without redundancy.

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 the rich annotations (covering safety and idempotency), 100% schema coverage, and the presence of an output schema (not shown but indicated in context signals), the description provides complete contextual information. It explains the tool's purpose, usage context, and provides examples without needing to duplicate structured data.

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%, so the schema already documents all 6 parameters thoroughly. The description provides examples that illustrate how parameters combine (e.g., action='balance_chart' with asset='BTC' and exchange='Binance'), adding some practical context beyond the schema's individual parameter descriptions.

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's purpose with a specific verb ('Get') and resource ('on-chain exchange data'), then elaborates on what can be tracked. It distinguishes this tool from siblings by focusing on exchange holdings and flows, unlike other tools that handle funding, liquidation, options, etc.

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 provides clear context for when to use the tool (tracking exchange holdings and flows) and includes examples that illustrate different use cases. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools.

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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