base_gas_priceCurrent Base mainnet gas price read live from JSON-RPC, in both wei and gwei. Use this to estimate the cost of a Base transaction before submitting it. Costs $0.005 USDC per call via x402 on Base; an unpaid call returns the payment challenge instead of data, and a call that returns no data is never settled so it costs nothing. Equivalent HTTP route: GET /gas.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds meaningful behavioral context beyond these: the $0.005 USDC cost, the payment challenge behavior for unpaid calls, and the no-settlement rule when no data is returned. This is valuable and not redundant.
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?
Three dense sentences with no filler: the core purpose, the use case, and the important cost/payment caveats. Every sentence earns its place and the key information is front-loaded.
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 zero-parameter read-only tool, the description covers the source, units, use case, cost behavior, and even the equivalent HTTP route. The lack of an output schema is not a significant gap at this complexity level.
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?
The tool has no parameters, so the schema is empty. The description still adds helpful semantics by specifying that the result is provided in both wei and gwei, which informs interpretation of the response.
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 states a specific verb ('read'), a precise resource ('Base mainnet gas price'), the live JSON-RPC source, and the output units (wei and gwei). This clearly distinguishes the tool from the sibling financial data tools.
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?
It explicitly tells the agent when to use the tool: to estimate the cost of a Base transaction before submitting it. It does not name alternatives, but with zero parameters and unrelated siblings, no exclusion is necessary.
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 resources: defi_protocol vs defi_protocols are clearly list-vs-detail, and crypto_spot_prices vs defi_token_prices are explicitly differentiated. The main overlap is prediction_market_search vs polymarket_markets/manifold_markets, but the cross-venue purpose is clearly stated.
All tool names use snake_case with a consistent resource-noun pattern (defi_, polymarket_, us_, etc.). Plural/singular variants are logical (defi_protocol vs defi_protocols, polymarket_market vs polymarket_markets), and no unconventional casing or verb-style mixing appears.
18 tools is slightly above the ideal 3-15 range, but the server covers a broad domain (crypto, DeFi, prediction markets, macro, FX, rates), so each tool serves a distinct data type. The count feels justified by the breadth rather than redundant.
The surface covers major market intelligence categories well: prices, yields, TVL, prediction markets, macro indicators, and FX. Minor gaps exist (e.g., no equities/commodities, limited macro series, no historical crypto data), but the core workflows for macro and market overview are supported without dead ends.