BeBraveBeKind/mcpskills-server
by Various
Pre-install trust layer for MCP servers, AI skills & npm packages — the @mcpskillsio/server MCP server (io.mcpskills/server).
MCP
BeBraveBeKind/mcpskills-server
Added 11 June 2026
Overview
A pre-install trust layer for MCP servers, AI skills, and npm packages. It is implemented as the @mcpskillsio/server MCP server (io.mcpskills/server) and runs in JavaScript environments. The tool aims to verify the trustworthiness of components before they are installed.
Best for
Best for
Developers who need a pre-install trust layer for MCP servers and related components
Use cases
- Verifying trust of MCP servers before deployment
- Screening AI skill packages for security issues
- Adding a trust check step to npm package installations
Notes
A pre-install trust layer for MCP servers, AI skills, and npm packages. It is implemented as the @mcpskillsio/server MCP server (io.mcpskills/server) and runs in JavaScript environments. The tool aims to verify the trustworthiness of components before they are installed.
0 stars on GitHub. Last updated 2026-06-09. Licensed MIT.
Use cases
- Verifying trust of MCP servers before deployment
- Screening AI skill packages for security issues
- Adding a trust check step to npm package installations
Pros
- Unified trust verification for three different software types
- Integrates directly with the MCP ecosystem
- Open source and publicly available on GitHub
Cons
- Zero stars indicates very limited community adoption so far
- Requires integration and may not work out-of-box with all workflows
- Trust mechanism depends on the specific implementation and may need vetting
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Unified trust verification for three different software types
- Integrates directly with the MCP ecosystem
- Open source and publicly available on GitHub
Cons
- Zero stars indicates very limited community adoption so far
- Requires integration and may not work out-of-box with all workflows
- Trust mechanism depends on the specific implementation and may need vetting
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