Historical OHLCV candles ($0.010 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| symbol | No | BTCUSDT | |
| payment | No | Optional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key. | |
| interval | No | 1d |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / paymentAdded value: +{
+ "description": "Optional. Base64 x402 payment payload you signed yourself (ERC-3009 TransferWithAuthorization, USDC on Base). Call without it once to receive the payment requirements, sign those, then call again with this argument. This server forwards the payload and never holds a key.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries responsibility for behavioral context. It does disclose that the tool costs $0.010 USDC, which is a meaningful behavioral trait about payment requirements. However, it does not mention the two-step payment flow (call first, receive requirements, sign and call again) described in the schema, nor does it state any rate limits or side effects. The payment workflow is available in the parameter description, so the marginal behavioral disclosure is above baseline but incomplete.
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 front-loads the essential purpose and price in a single readable phrase. There is no wasted text. It loses a point because it is almost too sparse, providing no structural context such as a short sentence about typical invocation, though conciseness itself is strong.
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 this tool has no output schema, no annotations, sparse parameter descriptions, and many sibling data tools, the one-line description leaves important gaps. An agent cannot tell how the returned candles are structured, whether the payment is per-request or per-candle, or how to distinguish this from similar market data retrievers. The two-step payment detail is in the schema, but the overall description does not make the tool self-sufficient especially without an output schema.
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 25% (only the payment parameter has a description). The tool description does not compensate by explaining interval, symbol, or limit, though the enum and defaults in the schema provide some hint. Given the low coverage, the description should have connected the params like interval/symbol to OHLCV semantics, but it simply does not.
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 'Historical OHLCV candles' clearly identifies the resource and the data type returned, and alongside the tool name 'get_historical' it is easy for an agent to infer this fetches past candlestick data. It distinguishes itself from sibling tools like get_crypto_prices or get_funding_rates by naming a concrete, unique object type (OHLCV candles). It loses a point because the description is a noun phrase rather than an explicit verb-driven sentence saying 'get' or 'fetch'.
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 is given about when to use this tool compared to sibling tools such as get_crypto_prices, get_technical_indicators, or get_signal_history_*. The description does not state any context, exclusions, or alternatives. The word 'historical' implies it is for past data, but this is left to inference rather than explicit direction.
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 clearly distinct metrics, but the paid/free sample pairs (get_crypto_prices/try_crypto_prices, etc.) and overlapping summary tools (get_market_overview, get_market_pulse, get_overnight_risk_brief) create some selection ambiguity. Descriptions list components, so an agent can disambiguate with effort, but the boundaries between bundles and single-purpose tools are not always obvious.
Tool names consistently follow a verb_noun pattern: get_ for data retrieval, try_ for free samples, and watch_condition for persistent monitoring. All names use lowercase snake_case with no mixed conventions, making the naming predictable and easy to navigate.
34 tools is well above the comfortable range for a typical MCP server and feels heavy even for a broad crypto data domain. The count is inflated by paid/free sample duplicates and multiple bundle variants that could have been consolidated.
The surface covers a wide range of crypto data: prices, funding, sentiment, arbitrage, derivatives, on-chain metrics, signal history, and monitoring. Minor gaps exist—such as no obvious generic signal discovery tool or order-book/trade-level data—but the core domain of market data with checkable records is thoroughly served.