crypto__exchange_rates
[Crypto Intelligence] Get current currency exchange rates. Args: base_currency: Base currency code (default 'USD')
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| base_currency | No | USD |
[Crypto Intelligence] Get current currency exchange rates. Args: base_currency: Base currency code (default 'USD')
| Name | Required | Description | Default |
|---|---|---|---|
| base_currency | No | USD |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. The description adds that rates are 'current' and that base_currency defaults to USD, which is consistent but does not disclose additional behavioral traits beyond 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 very short and to the point, using a prefix for categorization. Every part serves a purpose, though it could be slightly more structured.
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 optional parameter, read-only), the description is minimally adequate. However, it does not specify what exchange rates are returned (e.g., all currencies vs. a specific set) or the return format, which could leave ambiguity for the agent.
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 description adds meaning to the single parameter 'base_currency' by explaining it as a currency code with a default of 'USD'. Since schema description coverage is 0%, this provides essential context for selecting and using the parameter.
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 'Get current currency exchange rates' with a '[Crypto Intelligence]' prefix, indicating a crypto-specific scope. This distinguishes it from general exchange rate tools like 'finance__get_exchange_rates' but does not explicitly differentiate from 'crypto__crypto_prices'.
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 guidance on when to use this tool vs alternatives. There is no mention of when not to use or any prerequisites. The description is minimal and lacks usage context.
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.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.