kukapay/crypto-feargreed-mcp
by Various
Providing real-time and historical Crypto Fear & Greed Index data
MCP
kukapay/crypto-feargreed-mcp
Added 1 June 2026
Overview
This MCP server provides real-time and historical Crypto Fear & Greed Index data via the Model Context Protocol. It exposes tools that allow AI agents to query the current index value and historical data for sentiment analysis.
Best for
Best for
Developers building AI agents for crypto trading or sentiment analysis who need quick MCP access to the Fear & Greed Index.
Use cases
- Integrate Fear & Greed index into crypto trading agents
- Fetch historical sentiment data for strategy backtesting
- Monitor real-time market sentiment in AI dashboards
How to use
Install
npx -y @smithery/cli install @kukapay/crypto-feargreed-mcp --client claude Tested with
Claude Desktop
Example client config
{ \n "crypto-feargreed-mcp": { \n "command": "uv", \n "args": [ \n "--directory", "/your/path/to/crypto-feargreed-mcp", \n "run", \n "main.py" \n ]\n } \n} Notes
This MCP server provides real-time and historical Crypto Fear & Greed Index data via the Model Context Protocol. It exposes tools that allow AI agents to query the current index value and historical data for sentiment analysis.
53 stars on GitHub. Last updated 2025-05-10. Licensed MIT.
Use cases
- Integrate Fear & Greed index into crypto trading agents
- Fetch historical sentiment data for strategy backtesting
- Monitor real-time market sentiment in AI dashboards
Pros
- Delivers both real-time and historical index values
- Simple integration for any MCP-compatible runtime
- Lightweight Python implementation with clear API
Cons
- Requires an MCP-compatible AI agent framework to use
- Data accuracy depends entirely on the upstream Alternative.me source
- Only covers a single sentiment indicator, not comprehensive market data
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Delivers both real-time and historical index values
- Simple integration for any MCP-compatible runtime
- Lightweight Python implementation with clear API
Cons
- Requires an MCP-compatible AI agent framework to use
- Data accuracy depends entirely on the upstream Alternative.me source
- Only covers a single sentiment indicator, not comprehensive market data
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.