cex_dc_list_dc_contracts
List delivery contracts.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| settle | No | Settlement currency for delivery (e.g. usdt, btc) |
List delivery contracts.
| Name | Required | Description | Default |
|---|---|---|---|
| settle | No | Settlement currency for delivery (e.g. usdt, btc) |
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 this as read-only, idempotent, and non-destructive, so the safety profile is covered. However, the description adds no behavioral context such as return format, pagination, or whether results are filtered by the optional settle parameter. It provides no info beyond the literal action.
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 clear sentence with no fluff. It's concise and to the point, though it's minimal in detail. It earns its place but doesn't offer any structural enhancements.
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?
The tool is simple with one optional parameter and no output schema, but the description still feels incomplete. It doesn't explain what a delivery contract is, whether the settle parameter filters results or returns all when omitted, or what the response looks like. Given these gaps, the description is insufficient for full understanding.
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 covers the one parameter 'settle' with a clear description, achieving 100% schema description coverage, so the baseline is 3. The description doesn't add extra meaning, but it's not required given the schema is sufficient.
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 verb 'List' and the resource 'delivery contracts', making it evident what the tool does. It distinguishes from the sibling 'cex_dc_get_dc_contract' through the use of 'list' versus 'get', but it lacks an explicit 'all' or scope indicator, so it's not a full 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the optional 'settle' parameter's filtering role or contrast with other list tools (e.g., listing candlesticks or order books).
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.