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 ignaciohermosillacornejo · MCP Server · ★ 77
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is copilot-money-mcp safe to install? View the security audit →
Copilot Money MCP Server Query and manage your personal finances with AI using local Copilot Money data Disclaimer This is an independent, community-driven project and is not affiliated with, endorsed by, or associated with Copilot Money or its parent company in any way. This tool was created by an independent developer to enable AI-powered queries of locally cached data. "Copilot Money" is a trademark of its respective owner. [!NOTE] Copilot M
| Stars | 77 |
| Forks | 29 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 80.9318647366666/100 |
| Open Issues | 27 |
| Last Updated | 2026-08-31 |
| Created | 2026-01-11 |
| Platforms | mcp, node |
| Est. Tokens | ~17k |
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copilot-money-mcp is MCP server for Copilot Money App - AI powered personal finance queries using local data. It is categorized as a MCP Server with 77 GitHub stars.
copilot-money-mcp is primarily written in TypeScript. It covers topics such as bun, copilot-money, leveldb.
You can find installation instructions and usage details in the copilot-money-mcp GitHub repository at github.com/ignaciohermosillacornejo/copilot-money-mcp. The project has 77 stars and 29 forks, indicating an active community.
copilot-money-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to copilot-money-mcp on Agent Skills Hub include mesh, easy-mcp, gno. 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: