List Alpha tickers.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number | |
| limit | No | Maximum number of records returned in a single list | |
| currency | No | Query by specified currency name |
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?
The annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already convey the safety profile. The description adds no additional behavioral context, such as pagination behavior or what 'Alpha' means. It neither contradicts annotations nor provides beyond-annotation value.
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 short sentence with no waste or redundancy. It is concise but under-specified, omitting important details that could earn their place. Still, it is appropriately front-loaded and not verbose.
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 lack of an output schema and minimal description, the agent has no information about the return format or the meaning of 'Alpha' tickers. The tool is very simple, but the description leaves out key context that would help an agent understand what it is listing and what to expect.
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 input schema has 100% description coverage for all three parameters (page, limit, currency), so the description isn't required to explain them. The tool description adds no parameter semantics beyond the schema, which is acceptable per 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 'List Alpha tickers.' clearly states the verb (List) and resource (Alpha tickers), which is unambiguous. However, it doesn't distinguish this tool from sibling list tools like cex_alpha_list_alpha_currencies or cex_spot_get_spot_tickers, relying instead on the tool name for differentiation.
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?
No usage guidance is provided. The description does not indicate when to choose this tool over alternatives, nor does it mention any prerequisites or context. It simply states the action without helping the agent decide when to use it.
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.