get_price
Real-time crypto prices for 15,000+ coins (api_key required).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| vs | No | usd | |
| coins | No | bitcoin,ethereum | |
| api_key | No | Your API key from register() |
Real-time crypto prices for 15,000+ coins (api_key required).
| Name | Required | Description | Default |
|---|---|---|---|
| vs | No | usd | |
| coins | No | bitcoin,ethereum | |
| 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 / coins / descriptionRemoved value: -"Comma-separated coin IDs (e.g. bitcoin,ethereum)"Input schema / properties / vs / descriptionRemoved value: -"Vs currency (e.g. usd, eur)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must compensate. It states 'real-time' but does not disclose that it is a read-only operation, rate limits, data freshness, or any potential behavioral nuances. The implicit read nature is assumed but not stated.
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 extremely concise, using a single phrase with a parenthetical about api_key. It is front-loaded with the core purpose. However, some may argue it is too terse, but it earns its place without extraneous text.
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 should explain return values or format, but it does not. Given low schema coverage and limited behavioral info, the description is incomplete for an AI agent to fully understand the tool's context and effects.
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 description coverage is only 33% (only api_key has a description). The tool's description adds no extra meaning to parameters; it only mentions api_key requirement. For the vs and coins parameters, the schema provides defaults but no explanation, and the description does not compensate.
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 tool returns real-time crypto prices for over 15,000 coins, which is specific and distinguishes it from sibling tools like get_price_summary or get_coin. The verb 'get' and resource 'price' are well-defined.
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 mentions 'api_key required' but provides no guidance on when to use this tool versus alternatives like get_price_summary, get_coin, or other price-related siblings. There is no explicit context for usage decisions.
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.