crypto_pricesLive crypto prices (USD, 24h change, market cap) from CoinGecko. ~$0.005.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | No | Comma-separated coin ids, default bitcoin,ethereum,solana |
| Name | Required | Description | Default |
|---|---|---|---|
| result | No |
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 are present (readOnlyHint=false, openWorldHint=true, destructiveHint=false), and the description adds cost ('~$0.005') and source (CoinGecko). However, it doesn't disclose data freshness intervals, rate limits, or the oddity that readOnlyHint=false for a read-only operation. The description is minimal but not contradictory.
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?
One concise sentence that covers what, where, and cost. Highly efficient with no filler.
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?
The tool is simple with one optional parameter and an output schema exists, so the description doesn't need to explain return values. It mentions the key fields (USD, 24h change, market cap), source, and cost. Slightly incomplete due to the annotation mismatch, but overall sufficient for a simple price fetcher.
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 100% for the single 'ids' parameter, with its description already including format and default. The tool description adds no extra semantic meaning for the parameter, so baseline 3 is appropriate.
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 specifies the tool returns live crypto prices with USD, 24h change, and market cap from CoinGecko. It distinguishes itself from generic web tools by focusing on crypto data, though it doesn't explicitly name sibling alternatives like market_snapshot.
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 versus alternatives. It doesn't mention situations where this should be preferred (e.g., for CoinGecko data) or excluded (e.g., when broader market data is needed). The cost hint is useful but not a usage guideline.
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.
Most tools have clearly distinct purposes (image, music, video, vision, voice, etc.), but some overlap exists: ask_ai vs ask_ai_pro differ only in model strength, and web_search vs research_report both involve search with AI responses. Descriptions help clarify, though an agent could misselect in edge cases.
Tool names follow a mostly consistent snake_case pattern, with many using an 'ai_' prefix for generation tasks. However, name styles vary between verb_noun (call_endpoint, remove_bg) and noun_verb (crypto_prices, domain_info), and ask_ai/ask_ai_pro break the ai_ prefix convention. Minor deviations, but the overall pattern is readable.
At 16 tools, the server is slightly above the ideal 3-15 range but remains well-scoped for a multi-purpose utility server. Each tool has a distinct function, and the count feels manageable rather than overwhelming.
The server covers a broad set of capabilities (AI generation, web search, crypto, domain info), but it lacks lifecycle management for generated assets—there are no list/get/delete operations for previously created media, and the domain appears to be a collection of paid endpoints rather than a cohesive service.