LiquidVision — Crypto Derivatives Data

list_history_packages

Read-onlyIdempotent

[measured] Monthly Parquet history packages for backtests: liquidations (11 venues), funding hourly and settlements, open interest hourly, Hyperliquid and Lighter positions with liquidation prices — one file per dataset per month since 2026-07 with rows, bytes and sha256. Each entry has url (download with the API key in X-API-Key) and available for the caller's tier: Pro = this month and the previous one, Bot = all, free = none (use get_history for the last 24 h).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_history_packages"
  }
}

Input Schema

Name	Required	Description	Default
`api_key`	No	LiquidVision API key (lv_...). Omit when the key is sent as the X-API-Key header on the connection.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 6, 2026

addedInput schema / properties / api_key / description

Added value: +"LiquidVision API key (lv_...). Omit when the key is sent as the X-API-Key header on the connection."

AddedOct 16, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds important operational context beyond them: downloads require the API key in X-API-Key, entries include `url` and `available`, and availability depends on the caller's tier. There is no contradiction with the annotations.

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

Conciseness4/5

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

The description is front-loaded with the dataset scope and access rules, and every clause carries useful information. It is dense and could be easier to scan with bullets for datasets and tier rules, but it avoids filler.

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?

For a catalog/list tool with no output schema, the description is complete: it covers the datasets, file granularity, date range, entry fields, authentication, and tier-based availability. Nothing essential for calling or interpreting the result appears missing.

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 coverage is 100%, and the schema already explains that api_key can be omitted when sent via the X-API-Key header. The description reinforces the header authentication model but does not add constraints or meaning for the parameter beyond what the schema provides, so the baseline 3 is appropriate.

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 states a specific resource and format: 'Monthly Parquet history packages for backtests', enumerating datasets, one file per dataset per month since 2026-07, with rows, bytes, and sha256. It clearly distinguishes this catalog from get_history by positioning get_history as the last-24-hours alternative.

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?

It explains the intended use (backtests), names the key alternative for recent data ('use get_history for the last 24 h'), and gives explicit tier-based availability rules: Pro gets this month and the previous one, Bot gets all, free gets none. This is enough for an agent to choose correctly.

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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