mcp-skills
Related Servers
Alternatives to mcp-skills
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceEnables AI agents to autonomously search, evaluate, and install skills from the skills.sh catalog.44 npmISC
- AlicenseNot gradedqualityBmaintenanceEnables AI agents and IDEs to discover, install, and execute skills over Model Context Protocol via stdio or SSE, with semantic search and framework bridges.Apache 2.0
- AlicenseAqualityDmaintenanceConnects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.519 npm10MIT
- FlicenseNot gradedqualityDmaintenanceTransform any AI agent into a domain expert by giving it access to modular, reusable skills through the Model Context Protocol. Brings Claude's Skills format to any MCP-compatible agent, allowing you to create skills once and use them everywhere.21 npm30-
- AlicenseNot gradedqualityCmaintenanceAutomatically discovers and installs AI skills for your project's tech stack, supporting Claude, Copilot, Codex, and other MCP-compatible agents.7 npm4MIT
- AlicenseAqualityAmaintenanceModule discovery, documentation search, and skill generation for AI agents via the Model Context Protocol.22100 PyPI6GPL 3.0
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no overlap: analyzeProjectStack detects stacks, findSkills searches by keyword, selectSkill recommends for tasks, and install/uninstall/update manage skill lifecycle. The descriptions make it easy to differentiate between analysis, search, recommendation, and management functions.
Tools follow a consistent verbNoun pattern (e.g., analyzeProjectStack, findSkills, installSkill) with clear action-object naming. The minor deviation is 'selectSkill' which uses 'select' instead of a more precise verb like 'recommendSkill', but overall the naming is highly predictable and readable.
With 6 tools, the server is well-scoped for managing skills in the skills.sh ecosystem. It covers analysis, discovery, recommendation, and full lifecycle management (install/update/uninstall), with each tool earning its place without being overwhelming or insufficient for the domain.
The toolset provides complete coverage for the skills management domain: analyzeProjectStack for stack detection, findSkills and selectSkill for discovery and recommendation, and installSkill, updateSkill, uninstallSkill for full CRUD-like lifecycle management. No obvious gaps exist for the stated purpose.