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feargreed

Get the Crypto Fear & Greed Index to measure market sentiment and track investor psychology trends over the past 7 days.

Instructions

Crypto Fear & Greed Index — market sentiment indicator. Shows last 7 days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The getFearGreed function fetches the latest crypto Fear & Greed Index from the API.
    async function getFearGreed() {
      try {
        const data = await fetch('https://api.alternative.me/fng/?limit=7');
        return data.data.map(d => ({
          value: parseInt(d.value),
          label: d.value_classification,
          date: new Date(d.timestamp * 1000).toISOString().split('T')[0],
        }));
      } catch (e) {
        return { error: 'Fear & Greed API unavailable' };
      }
    }
  • index.js:310-314 (registration)
    Definition of the 'feargreed' tool in the MCP server tool list.
    {
      name: 'feargreed',
      description: 'Crypto Fear & Greed Index — market sentiment indicator. Shows last 7 days.',
      inputSchema: { type: 'object', properties: {} }
    }
  • The tool call handler for 'feargreed' calls the getFearGreed function.
    case 'feargreed':
      return await getFearGreed();
Behavior3/5

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 successfully communicates the temporal scope ('last 7 days'), but omits other behavioral traits such as whether the data is cached, rate limits, or the specific return format/structure.

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?

Two efficient sentences with zero waste. The first front-loads the identity (Fear & Greed Index), and the second specifies scope (last 7 days). No unnecessary verbiage or redundant phrases.

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 simple, parameterless data retrieval tool without output schema, the description covers the essential context: the specific index retrieved, its nature (sentiment), and the time window. While additional details on return format would be helpful, the current content is sufficient for tool selection and invocation.

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 contains zero parameters, triggering the baseline score of 4. The description appropriately does not invent parameters, and the empty schema correctly reflects the tool's parameterless nature.

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 clearly identifies the resource (Crypto Fear & Greed Index) and its function (market sentiment indicator), with specific scope (last 7 days). However, it does not explicitly differentiate from sibling tools like 'analyze' or 'trending' that might also deal with market sentiment.

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?

By labeling it a 'market sentiment indicator,' the description provides implied usage guidance (use when needing sentiment vs. raw price data). However, it lacks explicit when-to-use criteria, prerequisites, or comparisons to siblings like 'analyze' or 'trending'.

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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