get_top
Top coins by market cap (api_key required).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| vs | No | usd | |
| limit | No | ||
| api_key | No | Your API key from register() |
Top coins by market cap (api_key required).
| Name | Required | Description | Default |
|---|---|---|---|
| vs | No | usd | |
| limit | No | ||
| api_key | No | Your API key from register() |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / api_key / descriptionPrevious value: -"Optional — for billing"New value: +"Your API key from register()"Input schema / properties / api_key / descriptionAdded value: +"Optional — for billing"Input schema / requiredPrevious value: -[
- "api_key"
-]New value: +[]Input schema / properties / api_key / descriptionRemoved value: -"Your API key"Input schema / properties / limit / descriptionRemoved value: -"Number of coins (max 100)"Input schema / properties / vs / descriptionRemoved value: -"Currency"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only reveals that api_key is required, but does not disclose read-only nature, rate limits, or data source. Minimal behavioral transparency.
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?
Extremely concise at 5 words. No filler. However, could benefit from slight expansion for clarity.
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?
For a simple listing tool with 3 params and no output schema, description is minimal but covers core purpose. Lacks explanation of limit behavior or what constitutes 'top coins', but adequate for basic selection.
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?
Schema coverage is only 33% (only api_key has a description). Description adds no clarity for 'vs' or 'limit' parameters beyond the schema defaults. The mention of api_key required duplicates schema description.
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?
Description clearly states it returns top coins by market cap, which is a specific verb+resource. It distinguishes from sibling tools like get_top_gainers, get_top_losers, and get_trending by focusing on market cap ranking.
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?
Only mentions api_key requirement. No guidance on when to use this tool vs alternatives like get_trending or get_top_volume. No context on data freshness or suitability for different use cases.
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.
Tools generally have distinct purposes, but some overlap exists between price history tools (get_ohlc vs get_price_summary) and meme-related tools (analyze vs scan vs trending). Overall, descriptions help differentiate.
All tool names follow a consistent snake_case verb_noun pattern (e.g., get_price, set_price_alert, analyze_contract). No mixing of conventions.
48 tools is on the higher side, but it covers a broad spectrum of crypto data (prices, DeFi, sentiment, alerts, etc.) and each tool seems justified. However, the count could be slimmed down by grouping similar functions.
Very comprehensive coverage of crypto data: prices, market stats, DeFi, sentiment, gas, alerts, portfolio, arbitrage, token analysis. Minor gaps like NFT data or direct exchange rate queries.