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FinBridge

Compare Crypto Price Across Exchanges (Kimchi Premium)

compare_crypto_exchanges
Read-only

Compare the price of one crypto asset on two exchanges, converting both legs to USD, and report the premium of leg B over leg A. Classic use: the Korean "kimchi premium" — e.g. base:'BTC', exchange_a:'binance', quote_a:'USDT', exchange_b:'upbit', quote_b:'KRW' -> premium_pct is how much more expensive BTC is on upbit (in USD terms) than on binance.

Args:

  • base: asset symbol, e.g. 'BTC', 'ETH', 'XRP' (default BTC)

  • exchange_a / quote_a: first leg (defaults binance / USDT)

  • exchange_b / quote_b: second leg (defaults upbit / KRW)

  • Supported quotes: USD, USDT, USDC (treated as 1 USD, noted in output) and KRW (converted with the latest FRED DEXKOUS KRW-per-USD rate).

Returns: {base, legs:[{exchange, symbol, last, last_usd}], premium_pct, fx:{pair:'USD/KRW', rate, date, source:'FRED DEXKOUS'}, notes}. premium_pct = (leg_b_usd / leg_a_usd - 1) * 100.

Examples:

  • "what's the kimchi premium right now" -> defaults

  • "ETH premium bithumb vs kraken" -> {base:'ETH', exchange_a:'kraken', quote_a:'USD', exchange_b:'bithumb', quote_b:'KRW'}

  • Don't use for a single price (get_crypto_ticker) or history (get_crypto_ohlcv).

Errors: unknown symbol on either exchange -> check the exchange's market list (upbit/bithumb list KRW pairs only); unsupported quote currency lists the supported ones; FRED key missing blocks KRW conversion with a hint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoBase asset symbol, e.g. 'BTC', 'ETH'BTC
quote_aNoFirst-leg quote currency (USD | USDT | USDC | KRW)USDT
quote_bNoSecond-leg quote currency (USD | USDT | USDC | KRW)KRW
exchange_aNoFirst-leg exchange: binance | upbit | bithumb | coinbase | kraken | okx | bybit | gateio (default binance). Note: binance may be geo-blocked in some regions.binance
exchange_bNoSecond-leg exchange: binance | upbit | bithumb | coinbase | kraken | okx | bybit | gateio (default upbit). Note: binance may be geo-blocked in some regions.upbit

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fxNo
baseNo
legsYes
notesNo
premium_pctNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Annotations declare readOnlyHint and openWorldHint, so the safety profile is already established. The description adds substantial behavioral context: KRW conversion via FRED DEXKOUS, supported quote handling, premium formula, return structure, geo-blocking caveat, and error behavior for unknown symbols and missing FRED keys.

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 organized into clear sections — summary, Args, Returns, Examples, Errors — and every sentence earns its place. The core use case is front-loaded, and the examples and error notes are compact and directly actionable.

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?

The tool is complex with 5 optional parameters, output schema, and notable caveats, and the description covers all of it: parameter defaults, supported values, conversion method, return fields, formula, example mappings, and error handling. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description goes well beyond the schema. It explains the role of each leg, default pairings, how quote currencies are treated, and gives concrete examples that map natural language to parameter values. It also documents error conditions tied to parameter choices.

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 clear verb and resource: compare crypto asset prices across two exchanges, convert both legs to USD, and report premium. It differentiates itself from sibling tools by explicitly naming get_crypto_ticker and get_crypto_ohlcv as non-fit alternatives.

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?

The description gives explicit when-to-use guidance with the kimchi premium example and maps natural-language phrases to concrete argument sets. It also states exclusions: 'Don't use for a single price (get_crypto_ticker) or history (get_crypto_ohlcv).' This fully routes the agent.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct resource+action targets, and the overlapping screen_* tools are thoroughly cross-referenced with 'use screen_X instead' guidance. Minor ambiguity exists between get_disclosure_feed, get_dart_filings, and get_dart_major_events, which all surface KR filings from different angles but remain distinguishable.

Naming Consistency5/5

Every tool follows a consistent verb_noun snake_case pattern: get_* for retrievers, screen_* for screeners, search_* for lookups, plus action verbs like analyze_, backtest_, compare_, import_, and query_. Subfamilies (dart_*, edgar_*, fred_*, crypto_*) are consistently prefixed, making tool selection predictable.

Tool Count3/5

37 tools is heavy, and the four momentum screeners (canslim/kell/minervini/schwartz) plus three KR disclosure tools could arguably be collapsed into parameterized variants. However, the server's unusually broad scope—KR/US/TW/JP/EU equities, crypto, macro, portfolio, backtesting—means most tools earn their place, so the count is high but not chaotic.

Completeness4/5

The surface covers the core workflow well: search, prices, fundamentals, filings, insider trades, valuation, screeners, backtesting, and portfolio tracking for KR/US, plus crypto and macro. Notable gaps are the lack of single-company financial-statement tools for TW/JP/EU (only available through screen_companies) and no real-time stock quotes, but these are workable for the stated local-database research purpose.

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