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schoeffeljp

deribit-mcp

by schoeffeljp

get_volatility_index

Retrieve Deribit Volatility Index (DVOL) OHLCV data to track implied volatility trends for a selected currency over a specified time range.

Instructions

Get DVOL (Deribit Volatility Index) OHLCV data — Deribit's equivalent of the VIX. Shows implied volatility trend over time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
currencyYesCurrency
resolutionYesResolution: 1s, 1min, 1h, 12h, or 1D
end_timestampYesEnd timestamp in milliseconds since epoch
start_timestampYesStart timestamp in milliseconds since epoch

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It discloses that the output is OHLCV data representing implied volatility, which is useful, but it does not mention read-only status, date-range handling, response shape, or any limits or side effects.

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 only two sentences, front-loaded with the core action and resource. The VIX analogy and trend statement add value without becoming verbose, though the second sentence is somewhat redundant with 'OHLCV data'.

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

Completeness3/5

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

For a four-parameter read-only tool with no annotations and no output schema, the description explains the core concept and return type but omits response format details, behavior around timestamps and resolution, and how this differs from closely related tools like get_tradingview_chart_data or get_volatility_surface.

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%, with every parameter documented and enums provided for currency and resolution. The description adds DVOL context but no extra parameter-level meaning beyond what the schema already supplies.

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

Purpose4/5

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

The description names a specific resource (DVOL, Deribit's volatility index) and a specific output type (OHLCV data), with a helpful analogy to the VIX. It clearly identifies what the tool does, though it does not explicitly contrast itself with volatility-related siblings like get_historical_volatility or get_volatility_surface.

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

Usage Guidelines2/5

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

The description implies a use case ('shows implied volatility trend over time') but provides no explicit guidance on when to use this tool versus alternatives, no exclusions, and no routing among the many volatility and chart siblings.

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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