Hyperliquid funding rates + open interest across all perp markets. (x402: 0.001 USDC per call)
HTTP equivalent: GET /x402/perp-funding-aggregator Payment: x402 protocol — send X-PAYMENT header with base64 payment payload, or X-API-Key / X-Owner-Key / Bearer token to bypass.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only a title, so the description carries the transparency burden. It adds per-call cost (0.001 USDC), the HTTP GET equivalent, and detailed payment/authentication options. This goes beyond what annotations offer, though it doesn't mention response format or error behavior.
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 clear sentences plus two lines for HTTP/payment info, all relevant. It front-loads the core purpose and avoids redundancy. Every line contributes.
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 zero-parameter, no-output-schema context, the description covers the essential aspects: data content, cost, and access method. It lacks an explicit response structure, but the named data fields (funding rates, open interest) provide adequate context for a low-complexity 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?
The input schema is empty (0 params), so baseline is 4. The description's 'across all perp markets' clarifies that no filtering parameters exist, reinforcing the aggregate nature. No additional parameter explanation is needed.
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 'Hyperliquid funding rates + open interest across all perp markets,' clearly indicating a read endpoint that aggregates funding rates and OI for Hyperliquid perps. This distinguishes it from siblings like 'funding_rates' (generic) and 'hyperliquid_all_mids' (mid prices). The scope is explicit: all perp markets.
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 implies use for Hyperliquid perp funding data but doesn't explicitly state when to prefer it over alternatives like 'funding_rates' or 'binance_funding'. No when-not-to-use or alternative tool mentions are present, so the agent must infer usage.
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.
Multiple tool pairs are exact duplicates (e.g., wallet_analysis/wallet_analyzer, honeypot_check/rugpull_detector, defi_yield/defi_yield_rates) with identical descriptions, and many overlapping scanners (squeeze_scanner variants). An agent cannot reliably distinguish these tools.
Names are all snake_case, but conventions vary wildly: some are resource names (btc_price), some are actions (list_magnets), some are generic utilities (calculator), and duplicates use different naming patterns for the same function (wallet_analysis vs wallet_analyzer). No consistent verb_noun or resource_action pattern.
139 tools is an extreme count for any MCP server, far exceeding the 50+ threshold. The scope is a grab-bag of unrelated domains (crypto, FDA, SEC, utilities, web scraping), suggesting no curation.
The set is a shallow pile of read-only queries and utilities with no lifecycle management for any one domain. Many sub-areas have only one or two tools, and duplicates occupy slots where distinct operations should be. The lack of a clear domain makes completeness impossible to assess, but the surface is redundant rather than comprehensive.