pulsemcp verified Safe content atomic mcp-remote

Fear & Greed Index

This MCP server provides AI assistants with real-time access to the CNN Fear & Greed Index for US stock market sentiment analysis, built using TypeScript with the Model Context Protocol SDK and comprehensive market data fetching from CNN's production API. The implementation offers a single tool that retrieves the current composite Fear & Greed Index score (0-100 scale) along with seven individual market indicators including S&P 500 momentum, stock price strength and breadth, put/call options ratios, VIX volatility measures, junk bond demand, and safe haven demand, with historical comparisons for previous close, week, month, and year periods. Built with user-agent rotation for reliable data access, Zod schema validation for type safety, and flexible deployment options supporting both stdio and HTTP/SSE transports, it serves financial analysts needing conversational access to market sentiment data, traders requiring AI-assisted market psychology insights, and developers building financial applications that integrate real-time fear and greed metrics into automated decision-making workflows.

Cognium trust score

95%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: devops-ci
Source: PulseMCP
Repository: github.com/ycjcl868/mcp-server-fear-greed
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

View source Find related skills

MCP

Resolve Fear & Greed Index from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"