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VENTURE-AI-LABS

CryptoDataAPI MCP Server

get_options

Retrieve Bitcoin options market data to analyze open interest, volume, put/call ratios, and max pain price for informed trading decisions.

Instructions

Get BTC options market data including total open interest, volume, put/call ratio, and max pain price. A high put/call ratio (>1) suggests bearish hedging; low (<0.7) suggests bullish positioning. Max pain is the strike price at which most options expire worthless — price tends to gravitate toward max pain near expiry dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the get_options tool, which performs an API GET request to retrieve options market data.
    export async function handler(_args: z.infer<typeof schema>) {
      return apiGet("/api/v1/market-intelligence/options");
    }
  • The schema definition for the get_options tool, which accepts no arguments.
    export const schema = z.object({});
  • src/index.ts:28-46 (registration)
    The registration of the options tool within the main server entry point.
    import * as options from "./tools/options.js";
    
    // Prompts
    import * as marketBriefing from "./prompts/market-briefing.js";
    
    const tools = [
      daily,
      marketHealth,
      fearGreed,
      fundingRates,
      liquidations,
      openInterest,
      btcCycle,
      coinProfile,
      searchCoins,
      macro,
      stablecoinFlows,
      etfFlows,
      options,
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what data is returned and provides interpretive context about the metrics (bearish/bullish signals, max pain theory). However, it doesn't mention potential limitations like data freshness, source reliability, or rate limits that would be helpful for a read-only data tool.

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 efficiently structured with two sentences: the first states what data is returned, the second provides interpretive context. Every sentence adds value, though the interpretive guidance could be considered slightly beyond the minimal required scope for a pure data retrieval tool.

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

Completeness4/5

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 with no output schema, the description provides good contextual completeness. It clearly states what data is returned and adds valuable interpretive context. The main gap is the lack of information about data source, freshness, or format, which would help an agent understand the reliability and structure of the returned data.

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

Parameters4/5

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

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't waste space discussing non-existent parameters, focusing instead on what the tool returns and how to interpret the data.

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 the specific action ('Get BTC options market data') and lists the exact data points returned (total open interest, volume, put/call ratio, max pain price). It distinguishes itself from siblings like 'get_open_interest' by focusing specifically on options market data rather than general open interest.

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

Usage Guidelines3/5

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

The description implies usage context through its explanation of what the data means (e.g., 'high put/call ratio (>1) suggests bearish hedging'), but it doesn't explicitly state when to use this tool versus alternatives like 'get_open_interest' or 'get_market_health'. No explicit when-not-to-use guidance or prerequisite information is provided.

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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