cex_options_list_options_tickers
Get options tickers for an underlying
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| underlying | Yes | Underlying asset name, e.g. BTC_USDT |
Get options tickers for an underlying
| Name | Required | Description | Default |
|---|---|---|---|
| underlying | Yes | Underlying asset name, e.g. BTC_USDT |
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, idempotentHint, and destructiveHint, so the description adds no behavioral context beyond the purpose. It does not mention pagination, response format, or any special behavior. No contradiction with annotations, but the description carries no additional transparency burden.
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?
The description is a single sentence, immediately front-loaded with the action and resource, and contains no wasted words. It is concise and appropriately sized for a simple one-parameter tool.
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?
Given the tool's simplicity (one parameter, no output schema, annotations present), the description is minimally viable but lacks context about what the returned tickers represent or how this differs from similar list/underlying ticker tools. It is not misleading, but it does not fully help an agent select the correct tool among closely named siblings.
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?
The schema fully describes the only parameter 'underlying' with an example (BTC_USDT), so schema coverage is 100%. The description does not add any extra parameter semantics beyond what the schema already provides, which is the baseline for high 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 'Get options tickers for an underlying' uses a clear verb and resource, and specifies the target as an underlying asset. However, it does not distinguish from very similar sibling tools like cex_options_list_options_underlying_tickers, so it stops short of a 5.
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?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description simply states what the tool does without any usage context, leaving the agent to infer the intended use case from the name alone.
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.