"A server for finding information about skills and skill development" matching MCP servers:

Enables MCP clients to search skills.sh, view leaderboards, inspect skill details, retrieve third-party security audits, and browse official curated skills, with install commands for each result.

Transform 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.

MCP server implementing progressive disclosure for skill instructions, loading skills on-demand for token efficiency.

Exposes 79 cybersecurity skills and 12 orchestrator agents over MCP, with a typed 11-field output contract, an enforced resolvable-evidence gate (no verdict without a resolvable source), and human-approval gating for every mutating action. Apache-2.0, stdlib-only.

A package manager for AI agents that connects LLMs to a global registry of capabilities, allowing them to autonomously discover, install, and learn new skills from a centralized repository.

Enables agents to discover, read, and use reusable skills stored in public GitHub repositories.

Emulates Claude Skills with any LLM via MCP, enabling agents to use modular skill packages for specialized workflows and tool integrations.

An MCP server that generates skill manifests from GitHub skills directories and provides tools to recommend and download AI agent skills.

AI skills marketplace, management and connector

An MCP server that lets AI agents browse and fetch skills from remote registries — GitHub repositories or direct HTTP URLs — without installing them locally first.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides access to over 100 curated AI agent skills from organizations like Anthropic, Vercel, and Hugging Face. It enables AI assistants to perform specialized tasks including document processing, security analysis, and web development through a standardized interface.

Acts as a personal AI development environment manager, enabling workspace bootstrapping, headless skill and bundle installation, global caching, and health diagnostics.

Search, install, and manage AI agent skills (SKILL.md files) from GitHub repositories. Features workspace analysis for personalized recommendations and supports 140+ pre-indexed skills.

Enables AI agents to manage, search, plan, and execute reusable skills while automatically enforcing always-on coding and reasoning guidelines. It provides workflow orchestration, permission-controlled execution, dynamic skill registration, and feedback-based ranking.

Enables agents to discover, suggest, bind, and read local SKILL.md skills via MCP, while enforcing a maximum of three bound skills and a token budget to keep context small.

A Model Context Protocol server that enables seamless integration between Claude AI and development tools like VSCode, Augment, Vercel, Airtable, and Square.

A self-hosted registry and MCP server for reusable AI-agent skills that enables agents to discover, retrieve, and install skills with guardrails.