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Glama

Bitget MCP — Crypto, DeFi & Macro Market Intelligence

global_data

World data: forex exchange rates (150+ currencies), weather forecast, Wikipedia article summaries, arXiv paper search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoBase currency for forex (default: USD)
langNoWikipedia language (default: en)
limitNoMax results (1-20, default 5)
queryNoSearch query for wikipedia/arxiv
actionYes
symbolsNoComma-separated target currencies
latitudeNoLatitude for weather
longitudeNoLongitude for weather

TDQS

C2.9/5.0
Behavior2/5

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

No annotations provided, so description carries full burden. It only lists capabilities without disclosing behavioral traits like rate limits, data freshness, permissions, or side effects (though likely read-only). Lacks important context for agent decision-making.

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 effectively front-loads the purpose and lists specific data categories. No wasted words; highly efficient.

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

Completeness2/5

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

For a multi-action tool with 8 parameters and no output schema, the description is too brief. It does not explain parameter dependencies per action (e.g., weather requires lat/lon) or return format, leaving agents underinformed.

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 88%, so the input schema documents most parameters. The description adds no extra meaning beyond listing the four actions, which is already captured in the 'action' enum.

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?

Description lists four distinct data domains (forex, weather, Wikipedia, arXiv) with specific details like number of currencies. It clearly states what the tool provides, distinguishing it from siblings that focus on single domains.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like 'forex' or 'weather' tools. The description does not mention prerequisites, typical scenarios, or exclusions.

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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TDQS

B3/5.0
Disambiguation3/5

Multiple tools overlap in providing crypto price data (crypto_price, crypto_market, crypto_derivatives, global_assets) and news (news_feed, tradfi_news). While descriptions clarify some differences, agents may struggle to choose between similar tools.

Naming Consistency2/5

Tool names mix styles: some are simple nouns (backtest, cn_market), others compound nouns with underscores (crypto_derivatives, derivatives_sentiment). No consistent verb_noun pattern, making it harder to infer purpose from name alone.

Tool Count3/5

With 19 tools covering a broad domain (crypto, DeFi, macro), the count feels slightly high but justifiable. However, several tools could be merged to reduce overlap and improve navigability.

Completeness4/5

The tool set covers a wide range of market intelligence needs: price data, technical analysis, sentiment, macro indicators, news, and DeFi. Minor gaps like on-chain analytics or direct trading are acceptable given the intelligence focus.

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