CryptoDataAPI MCP Server

get_fear_greed

Retrieve the Crypto Fear & Greed Index to assess market sentiment, identify potential buying opportunities during extreme fear, and detect overheated markets during extreme greed.

Instructions

Get the Crypto Fear & Greed Index — a multi-source averaged sentiment score from 0 (Extreme Fear) to 100 (Extreme Greed). Classifications: Extreme Fear (0-25), Fear (26-40), Neutral (41-60), Greed (61-75), Extreme Greed (76-100). Includes per-source breakdown. Extreme Fear often signals buying opportunities; Extreme Greed often signals overheated markets.

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": "get_fear_greed"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Implementation Reference

src/tools/fear-greed.ts:14-16 (handler)

The handler function for get_fear_greed tool.

export async function handler(_args: z.infer<typeof schema>) {
  return apiGet("/api/v1/sentiment/fear-greed");
}

src/tools/fear-greed.ts:12-12 (schema)
The schema definition for get_fear_greed tool.
```
export const schema = z.object({});
```
src/tools/fear-greed.ts:4-4 (registration)
The registration name for get_fear_greed tool.
```
export const name = "get_fear_greed";
```

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 23, 2026

TDQS

A4.4/5.0

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 and does so well. It discloses behavioral traits: the tool returns a sentiment score with classifications, includes a per-source breakdown, and offers interpretive guidance on market implications (e.g., Extreme Fear signals buying opportunities). No contradictions exist.

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 front-loaded with the core purpose, followed by detailed classifications and practical insights. Every sentence adds value—defining the index, explaining its scale, detailing classifications, and providing market context—with zero waste.

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?

Given the tool's simplicity (0 parameters, no output schema), the description is nearly complete. It explains what the tool returns and its significance, though it could briefly mention the data format or update frequency for full completeness.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics, explaining the score range and classifications, which adds value beyond the schema.

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 tool's purpose: to retrieve the Crypto Fear & Greed Index, specifying it's a multi-source averaged sentiment score with a 0-100 range. It distinguishes this from siblings by focusing on market sentiment rather than specific assets, cycles, or financial metrics.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool—to assess market sentiment—and implicitly suggests alternatives by mentioning classifications like 'buying opportunities' or 'overheated markets.' However, it doesn't explicitly name when not to use it or direct alternatives among 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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