No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by wshobson · MCP Server · ★ 668
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is maverick-mcp safe to install? View the security audit →
MaverickMCP - Personal Stock Analysis MCP Server MaverickMCP is a personal-use FastMCP 2.0 server that provides professional-grade financial data analysis, technical indicators, and portfolio optimization tools directly to your Claude Desktop interface. Built for individual traders and investors, it offers comprehensive stock analysis capabilities without any authentication or billing complexity. The server comes pre-seeded with all 520 S&P 500 stocks and provides advanced screening recommendations across multiple strategies. It runs locally with HTTP/SSE/STDIO transport options for seamless integration with Claude Desktop and other MCP clients. Why MaverickMCP? MaverickMCP provides professional-grade financial analysis tools directly within your Claude D
| Stars | 668 |
| Forks | 157 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.9839665662793/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-13 |
| Created | 2025-08-24 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~21k |
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maverick-mcp is MaverickMCP - Personal Stock Analysis MCP Server. It is categorized as a MCP Server with 668 GitHub stars.
maverick-mcp is primarily written in Python. It covers topics such as ai-agents, algorithmic-trading, anthropic.
You can find installation instructions and usage details in the maverick-mcp GitHub repository at github.com/wshobson/maverick-mcp. The project has 668 stars and 157 forks, indicating an active community.
maverick-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to maverick-mcp on Agent Skills Hub include open-trading-api, ai-trader, atlassian-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: