market_snapshotCrypto market snapshot in one call: prices + fear/greed + trending + BTC fees. ~$0.02.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | No | Coin ids to include |
| 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?
Annotation Contradiction: The annotation declares readOnlyHint=false, yet the description characterizes the tool as a 'snapshot' which implies read-only, non-mutating behavior. This is a direct contradiction. The cost disclosure (~$0.02) is useful but does not resolve the inconsistency.
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 and well-structured: the first sentence conveys the complete functionality, the second adds pricing. Every word earns its place with no fluff.
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, one-optional-parameter tool with an output schema, the description covers the key features and pricing. However, the contradiction with the readOnlyHint annotation leaves a gap about side effects, slightly reducing completeness.
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 for the single optional 'ids' parameter is 100%, with the schema already providing 'Coin ids to include'. The description adds no additional parameter semantics, but the high schema coverage justifies a baseline score of 3.
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's purpose: a single-call crypto market snapshot combining prices, fear/greed index, trending, and BTC fees. It uses a specific verb ('snapshot') and enumerates the resources, effectively distinguishing it from the sibling crypto_prices tool which likely only provides price data.
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 phrase 'in one call' implies usage for consolidated market data retrieval, making it clear when to prefer this over separate price queries. While it doesn't explicitly name alternatives or exclusions, the sibling context and the description provide sufficient 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.
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.