[Crypto Intelligence] Get current cryptocurrency prices and market data from CoinGecko. Args: coins: List of coin IDs (e.g. ['bitcoin', 'ethereum']). Empty for top coins. max_results: Max results (default 50)
| Name | Required | Description | Default |
|---|---|---|---|
| coins | No | ||
| max_results | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set readOnlyHint=true and openWorldHint=true. The description adds that it uses CoinGecko and that an empty coins list yields top coins, but does not disclose other behavioral traits like rate limits, data freshness, or error handling. It provides minor context 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 concise, using a bracketed tag '[Crypto Intelligence]' for categorization, and an 'Args:' section for parameters. Each sentence is functional, though the structure could be slightly more formal.
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?
With no output schema, the description does not specify the return format or fields, leaving the agent to infer from 'prices and market data'. This is adequate for a simple fetch tool but lacks completeness for precise 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?
Despite 0% schema description coverage, the description explains each parameter: 'coins: List of coin IDs (e.g. ['bitcoin', 'ethereum']). Empty for top coins.' and 'max_results: Max results (default 50)'. This adds significant meaning beyond the schema's type and default values.
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 cryptocurrency prices and market data from CoinGecko', specifying the verb (Get), resource (prices and market data), and data source (CoinGecko). However, it does not differentiate from the sibling tool 'finance__get_crypto_prices', which likely has a similar purpose.
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?
Provides a usage hint: 'Empty for top coins' for the coins parameter, indicating common usage. No explicit guidance on when to use this tool versus alternatives like 'crypto__exchange_rates' or 'finance__track_crypto_portfolio', nor when not 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.
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.