Get ticker information for one or all currency pairs
| Name | Required | Description | Default |
|---|---|---|---|
| timezone | No | Timezone, e.g. Asia/Shanghai. Affects the time range of statistics | |
| currency_pair | No | Currency pair name, e.g. BTC_USDT. Returns all pairs if not specified |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safe-read nature is known. The description adds that the tool returns tickers for one or all pairs, but it does not disclose behavioral traits like timezone effects on statistics or return format. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded and contains no fluff. Every word earns its place, making it easily scannable for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and simple optional parameters, the description is adequate but not complete. It does not describe what ticker information includes (e.g., last price, volume) or how timezone affects results. The annotations mitigate safety concerns but not return semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters (timezone, currency_pair) having descriptions. The tool description adds nothing beyond the schema, except the implicit 'one or all' scope already reflected in the currency_pair description. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('ticker information'), and defines the scope ('one or all currency pairs'). This distinguishes it from sibling tools like cex_spot_get_currency_pair, which retrieves pair details rather than tickers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Given many sibling tools (e.g., cex_fx_get_fx_tickers, cex_options_list_options_tickers) also offer ticker data, the absence of differentiation or explicit use cases leaves the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool is clearly scoped by its domain prefix (spot, fx, options, etc.) and resource type, with no two tools serving the same purpose. Even similar data types like candlesticks and order books are unambiguously separated by market.
The naming follows a strong pattern: cex_<domain>_<verb>_<resource>. However, the use of 'get' vs 'list' is occasionally inconsistent (e.g., cex_fx_get_fx_tickers vs cex_spot_list_currencies), and some names are verbose with version suffixes like 'v4'.
With 63 tools, this is an extreme count that will overwhelm an agent. While the breadth covers many product lines, the vast number of endpoints makes selection difficult and violates the typical scope for an MCP server.
The tool surface comprehensively covers public market data across spot, futures, options, delivery, earn, margin, lending, launch, and social products. Minor gaps exist (e.g., no historical trade depth, no single-ticker convenience methods), but the core data needs are fully addressed.