Stockscreen (Yahoo Finance)
This StockScreen MCP server, developed by Todd Wolven, provides AI assistants with advanced stock screening capabilities using data from Yahoo Finance. Built with Python and leveraging libraries like yfinance and pandas, it offers a flexible interface for technical, fundamental, and options-based stock analysis. The server implements customizable screening criteria, watchlist management, and result storage functionalities. It's designed to handle various market cap categories and ETFs, with robust error handling and rate limiting. This implementation is particularly valuable for financial analysts, algorithmic traders, and AI researchers working on quantitative finance applications, enabling use cases such as automated trading strategy development, portfolio optimization, and market trend analysis.
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 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- finance
- Source
- PulseMCP
- Repository
- github.com/twolven/mcp-stockscreen
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Stockscreen (Yahoo Finance) 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--scope user for --scope project to commit it to .mcp.json.