cex_mcl_get_multi_collateral_fix_rate
Get available fixed interest rates for multi-collateral loans (public)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get available fixed interest rates for multi-collateral loans (public)
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 read-only, idempotent, and non-destructive hints. The description adds value by noting '(public)', clarifying that the endpoint requires no authentication. It does not describe return structure or pagination, but given the annotations, the behavioral disclosure is adequate.
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, front-loaded sentence with no redundant information. Every word serves a purpose, and the parenthetical '(public)' adds essential context without bloat.
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 low complexity (no parameters, simple read operation) and the presence of comprehensive annotations, the description is sufficient. It clearly states what the tool returns (fixed rates) and the public nature, though it stops short of describing the exact response format. For such a simple tool, this level of detail is complete enough.
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 tool has zero parameters, so per the baseline, a score of 4 is appropriate. The description correctly focuses on the output concept (fixed interest rates) without needing to explain parameter details.
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 ('Get') with a clear resource ('available fixed interest rates for multi-collateral loans') and adds scope ('public'). It distinguishes this tool from similar siblings like 'cex_mcl_get_multi_collateral_current_rate' by specifying 'fixed' rates, making the purpose unambiguous.
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 implies usage for retrieving fixed rates but provides no explicit when-to-use or exclusion guidance. It does not mention the alternative 'current_rate' tool, leaving the agent to infer the distinction. For a zero-parameter public endpoint, this is acceptable but not exemplary.
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.