finance

Fear & Greed Index

ycjcl868

by ycjcl868

Access CNN's Fear & Greed Index for US stock market sentiment, including Dow Jones Industrial Average index momentum and

Provides real-time access to CNN's Fear & Greed Index for US stock market sentiment analysis, retrieving current composite scores and seven individual market indicators including S&P 500 momentum, options ratios, and volatility measures with historical comparisons.

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Real-time CNN dataSeven detailed market indicatorsHistorical comparisons included

best for

  • / Stock traders analyzing market sentiment
  • / Financial analysts tracking market fear levels
  • / Investment researchers studying market psychology
  • / Portfolio managers timing market entries

capabilities

  • / Fetch current Fear & Greed Index score (0-100)
  • / Get historical sentiment comparisons
  • / Access seven individual market indicators
  • / Retrieve S&P 500 momentum data
  • / Monitor options put/call ratios
  • / Track VIX volatility measures

what it does

Retrieves real-time CNN Fear & Greed Index data to analyze US stock market sentiment. Provides both the main composite score and seven individual market indicators like VIX volatility and put/call ratios.

how to install

You can install Fear & Greed Index in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

Fear & Greed Index is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

MCP Server Fear & Greed Index

NPM Downloads

Install MCP Server

A Model Context Protocol (MCP) server that provides access to the CNN Fear & Greed Index for the US stock market. This server fetches real-time market sentiment data and presents it in both structuredContent and text content.

Features

  • Real-time Fear & Greed Index: Get the current market sentiment score (0-100)
  • Historical Comparisons: View previous close, week, month, and year data
  • Detailed Market Indicators: Access individual component scores including:
    • Market Momentum (S&P 500 & S&P 125)
    • Stock Price Strength & Breadth
    • Put/Call Options Ratio
    • Market Volatility (VIX)
    • Junk Bond Demand
    • Safe Haven Demand
  • Flexible Output: Choose between structured markdown or raw JSON format

Requirements

  • Node.js 18 or newer
  • VS Code, Cursor, Windsurf, Claude Desktop or any other MCP client

Getting Started

Local (Stdio)

First, install the Fear & Greed MCP server with your client. A typical configuration looks like this:

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-fear-greed@latest"
      ]
    }
  }
}
<details><summary><b>Install in VS Code</b></summary>

You can also install the mcp-server-fear-greed MCP server using the VS Code CLI:

# For VS Code
code --add-mcp '{"name":"mcp-server-fear-greed","command":"npx","args":["mcp-server-fear-greed@latest"]}'

After installation, the Fear & Greed MCP server will be available for use with your GitHub Copilot agent in VS Code.

</details> <details> <summary><b>Install in Cursor</b></summary>

Go to Cursor Settings -> MCP -> Add new MCP Server. Name to your liking, npx mcp-server-fear-greed. You can also verify config or add command like arguments via clicking Edit.

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "command": "npx",
      "args": [
        "mcp-server-fear-greed@latest"
      ]
    }
  }
}
</details> <details> <summary><b>Install in Windsurf</b></summary>

Follow Windsurf MCP documentation. Use following configuration:

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "command": "npx",
      "args": [
        "mcp-server-fear-greed@latest"
      ]
    }
  }
}
</details> <details> <summary><b>Install in Claude Desktop</b></summary>

Follow the MCP install guide, use following configuration:

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "command": "npx",
      "args": [
        "mcp-server-fear-greed@latest"
      ]
    }
  }
}
</details>

Remote (SSE / Streamable HTTP)

At the same time, use --port $your_port arg to start the browser mcp can be converted into SSE and Streamable HTTP Server.

# normal run remote mcp server
npx mcp-server-fear-greed --port 8089

You can use one of the two MCP Server remote endpoint:

  • Streamable HTTP(Recommended): http://127.0.0.1::8089/mcp
  • SSE: http://127.0.0.1::8089/sse

And then in MCP client config, set the url to the SSE endpoint:

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "url": "http://127.0.0.1::8089/sse"
    }
  }
}

url to the Streamable HTTP:

{
  "mcpServers": {
    "mcp-server-fear-greed": {
      "type": "streamable-http", // If there is MCP Client support
      "url": "http://127.0.0.1::8089/mcp"
    }
  }
}

In-memory call

If your MCP Client is developed based on JavaScript / TypeScript, you can directly use in-process calls to avoid requiring your users to install the command-line interface to use Fear & Greed MCP.

import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { InMemoryTransport } from '@modelcontextprotocol/sdk/inMemory.js';

// type: module project usage
import { createServer } from 'mcp-server-fear-greed';
// commonjs project usage
// const { createServer } = await import('mcp-server-fear-greed')

const client = new Client(
  {
    name: 'test fear greed client',
    version: '1.0',
  },
  {
    capabilities: {},
  },
);

const server = createServer();
const [clientTransport, serverTransport] = InMemoryTransport.createLinkedPair();

await Promise.all([
  client.connect(clientTransport),
  server.connect(serverTransport),
]);

// list tools
const result = await client.listTools();
console.log(result);

// call tool
const toolResult = await client.callTool({
  name: 'get_fear_greed_index',
  arguments: {
    format: 'json'
  },
});
console.log(toolResult);

API Reference

Tool: get_fear_greed_index

Fetches the current Fear & Greed Index and related market indicators.

Parameters

  • format (optional): Output format
    • "structured" (default): Returns formatted markdown with organized data
    • "json": Returns raw JSON data

Example Usage

// Get structured output
await client.callTool("get_fear_greed_index");

// Get JSON output
await client.callTool("get_fear_greed_index", { format: "json" });

Response Structure

The tool returns data in the following structure:

{
  "fear_and_greed": {
    "score": 75,
    "rating": "greed",
    "timestamp": "2025-07-18T23:59:57+00:00",
    "previous_close": 75.31,
    "previous_1_week": 75.26,
    "previous_1_month": 54.29,
    "previous_1_year": 45.94
  },
  "fear_and_greed_historical": {
    "timestamp": 1752883197000,
    "score": 75,
    "rating": "greed"
  },
  "market_momentum_sp500": {
    "timestamp": 1752871567000,
    "score": 61.2,
    "rating": "greed"
  },
  "market_momentum_sp125": {
    "timestamp": 1752871567000,
    "score": 61.2,
    "rating": "greed"
  },
  "stock_price_strength": {
    "timestamp": 1752883197000,
    "score": 80,
    "rating": "extreme greed"
  },
  "stock_price_breadth": {
    "timestamp": 1752883197000,
    "score": 84,
    "rating": "extreme greed"
  },
  "put_call_options": {
    "timestamp": 1752871897000,
    "score": 79.6,
    "rating": "extreme greed"
  },
  "market_volatility_vix": {
    "timestamp": 1752869701000,
    "score": 50,
    "rating": "neutral"
  },
  "market_volatility_vix_50": {
    "timestamp": 1752869701000,
    "score": 50,
    "rating": "neutral"
  },
  "junk_bond_demand": {
    "timestamp": 1752877800000,
    "score": 88.8,
    "rating": "extreme greed"
  },
  "safe_haven_demand": {
    "timestamp": 1752868799000,
    "score": 81.4,
    "rating": "extreme greed"
  }
}

Fear & Greed Index Ratings

The index uses the following rating scale:

  • 0-25: Extreme Fear
  • 26-45: Fear
  • 46-55: Neutral
  • 56-75: Greed
  • 76-100: Extreme Greed

Development

Access http://127.0.0.1:6274/:

npm run dev

Error Handling

The server includes comprehensive error handling:

  • Network request failures are caught and reported
  • Invalid API responses are handled gracefully
  • Missing data fields are filled with sensible defaults
  • All errors include descriptive messages

FAQ

What is the Fear & Greed Index MCP server?
Fear & Greed Index is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Fear & Greed Index?
This profile displays 35 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.735 reviews
  • Dhruvi Jain· Dec 28, 2024

    Fear & Greed Index reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Valentina Agarwal· Dec 16, 2024

    Fear & Greed Index is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Oshnikdeep· Nov 19, 2024

    I recommend Fear & Greed Index for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Anika Diallo· Nov 19, 2024

    According to our notes, Fear & Greed Index benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Meera Martinez· Nov 7, 2024

    Fear & Greed Index is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Meera Zhang· Oct 26, 2024

    We evaluated Fear & Greed Index against two servers with overlapping tools; this profile had the clearer scope statement.

  • Ganesh Mohane· Oct 10, 2024

    Strong directory entry: Fear & Greed Index surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Soo Flores· Oct 10, 2024

    Fear & Greed Index has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Mia Jain· Sep 21, 2024

    Fear & Greed Index reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Meera Diallo· Sep 17, 2024

    Useful MCP listing: Fear & Greed Index is the kind of server we cite when onboarding engineers to host + tool permissions.

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