Skills-MCP-Server
MCP ServerFreeIndex and search reusable skills from local folders. Discover relevant skills with fast keyword ranking and load their content on demand. Keep workflows portable and offline-friendly while sharing skills across projects.
Capabilities3 decomposed
keyword-based skill indexing
Medium confidenceThis capability utilizes a local indexing mechanism that ranks reusable skills based on keyword relevance, allowing for quick retrieval. It employs a lightweight search algorithm that scans local folders for skill definitions and metadata, ensuring that users can discover relevant skills efficiently without relying on external servers. This local-first approach enhances portability and offline access.
The local indexing mechanism is optimized for keyword ranking, allowing for rapid skill discovery without cloud dependencies.
More efficient than cloud-based solutions for local skill discovery due to reduced latency and offline capabilities.
on-demand skill loading
Medium confidenceThis capability allows users to load skill content dynamically when needed, rather than preloading all skills at startup. It uses a lazy-loading pattern that fetches skill definitions from local storage only when a specific skill is requested, minimizing memory usage and improving startup times.
Utilizes a lazy-loading architecture that fetches skill content only when required, optimizing resource usage.
More efficient than traditional preloading methods, reducing memory footprint and startup time.
cross-project skill sharing
Medium confidenceThis capability enables the sharing of indexed skills across different projects by maintaining a centralized skill repository structure. It allows users to reference skills from various local folders, promoting reusability and collaboration without duplicating skill definitions.
Centralized skill repository structure facilitates easy cross-project sharing without redundancy.
More streamlined than manual copying of skills, reducing maintenance overhead and versioning issues.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓developers managing multiple projects with reusable skills
- ✓developers building applications with numerous skills that may not all be used at once
- ✓teams working on multiple projects that require shared skill sets
Known Limitations
- ⚠Indexing performance may degrade with very large skill sets due to linear search algorithms
- ⚠Initial loading time for the first skill may be longer due to fetching from disk
- ⚠Requires careful management of skill versions to avoid conflicts
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
Repository Details
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Index and search reusable skills from local folders. Discover relevant skills with fast keyword ranking and load their content on demand. Keep workflows portable and offline-friendly while sharing skills across projects.
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