Live crypto prices and market data: spot price, market cap, 24h volume and change for any coins (Bitcoin, Ethereum, Solana, altcoins). Call for any price, market cap or volume question.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes | Coin IDs as lowercase slugs, e.g. ['bitcoin','ethereum','solana'] | |
| vs_currency | No | Quote currency, defaults to 'usd' |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds behavioral context by emphasizing 'live' data and listing specific market metrics, which helps the agent understand the return value scope beyond the base safety hints.
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 two sentences long, concise and front-loaded with the key purpose. Every sentence adds value, though the second sentence could be slightly more concise without losing meaning.
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?
Given the tool has a clear market data focus, complete schema, and an output schema (not shown here), the description sufficiently covers when and how to use it. It doesn't detail every edge case but provides enough context for a straightforward data retrieval tool.
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%, so the schema already documents both parameters. The description reinforces that 'ids' is for coin slugs and 'vs_currency' is for quote currency, but adds no new semantic meaning beyond the schema—keeping the score at baseline 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 provides live crypto prices and market data, listing specific metrics like spot price, market cap, 24h volume, and change. It also mentions specific coins (Bitcoin, Ethereum, Solana, altcoins) and distinguishes it from sibling tools with different focuses like 'get_btc_network' or 'get_fear_greed'.
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 clearly indicates when to use this tool—for any price, market cap, or volume question. It doesn't explicitly state when not to use it or list alternatives among siblings, but given the broad scope and clear market data focus, usage context is well implied.
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 target distinct domains (network, market, derivatives, macro, on-chain flows), and overlapping tools like get_derivatives vs get_derivatives_aggregate are clearly differentiated by scope and detail level. However, get_crypto_market and get_market_dominance both cover market-wide data, and get_btc_network and get_eth_whale_flows both touch on-chain activity, which could cause some confusion.
All tool names follow a consistent get_ prefix with descriptive nouns (e.g., get_btc_network, get_defi_overview, get_execution_cost). The pattern is uniform across all 16 tools, with no camelCase or inconsistent verb styles, making it very predictable for an agent.
With 16 tools, the server covers a broad but coherent domain of crypto market analysis—prices, on-chain, derivatives, macro, sentiment, and execution. Each tool addresses a distinct analytical need, and the count is well-scoped for a comprehensive agent, not excessive given the breadth of features.
The surface is remarkably complete for a market analysis agent, covering spot, derivatives, on-chain, macro, sentiment, history, and execution costs. Minor gaps exist: no direct tool for decentralized exchange (DEX) trading volumes or specific coin list discovery, and no tool for order book depth beyond the execution cost tool. However, agents can work around these with existing tools.