List all options contracts for an underlying
| Name | Required | Description | Default |
|---|---|---|---|
| expiration | No | Unix timestamp of expiration date | |
| 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well-covered. The description adds minimal behavioral context beyond stating the listing scope (for an underlying) and does not disclose any unexpected side effects or additional behavior. 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?
The description is a single, focused sentence of only seven words. It is fully front-loaded and contains no filler, making it highly efficient and easy to parse.
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?
For a simple two-parameter listing tool with full schema coverage and strong annotations, the description is adequate. It does not mention the optional expiration filter or response format, but the schema fills those gaps, and the tool's simplicity means minimal additional context is needed.
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% so both parameters (underlying and expiration) are already documented in the schema. The description adds no additional parameter semantics or examples beyond the schema, so it does not exceed the baseline.
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 uses a specific verb ('List') and resource ('options contracts') with a clear scope ('for an underlying'), making its purpose immediately obvious. It also distinguishes itself from sibling tools like cex_options_get_options_contract (singular retrieval) and cex_options_list_options_tickers (different resource) by emphasizing 'all contracts'.
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 clearly indicates when to use the tool: when you need all options contracts for a given underlying. It does not explicitly mention alternatives or exclusions, but the naming and 'all' clearly differentiate it from the singular get_options_contract sibling, providing strong contextual usage guidance.
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.