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hyperevm-mcp

hyperevm-mcp

by sand0vvv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

Funding history

hl_funding
Read-onlyIdempotent

Assess funding rate history for Hyperliquid perps to determine durability of spreads, including average, range, percent positive, and comparison with Binance/Bybit predictions.

Instructions

Funding rate history for one Hyperliquid perp — how the rate actually behaved over the past days, not just its value right now: average, range, how much of the time it stayed positive, and what holding the position would have paid. Includes the current predicted rate on Binance and Bybit for comparison. Use this when the question is whether a funding spread is durable rather than what it is this hour. Read-only, public data, no API key.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "hl_funding"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoHow far back to look. Default 7, maximum 14.
symbolYesPerp symbol, e.g. BTC or HYPE.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, openWorldHint, etc., but the description adds context: includes Binance/Bybit comparison, historical behavior details. No contradiction with annotations. Slightly reduced because annotations already cover safety profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded paragraph of four sentences. Every sentence provides essential information without redundancy, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, but description sufficiently explains return data (average, range, positivity, holding cost, Binance/Bybit comparison). For a read-only data retrieval tool with strong annotations, this is complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, baseline 3. The description does not add extra meaning beyond the schema—it only implicitly mentions 'how far back' which is already described in the schema. No additional semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides funding rate history for a Hyperliquid perp, specifying metrics like average, range, positivity, and holding cost. It distinguishes from just current rate by highlighting historical behavior, which differentiates it from siblings like hl_market.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises 'Use this when the question is whether a funding spread is durable rather than what it is this hour.' Also states it is read-only, public data, no API key needed, providing clear when-to-use and preconditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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