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

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

Dynamically loads and exposes skills from a directory with hot-reloading support, enabling users to manage and query skill content via MCP resources and tools.

MCP server that unifies and synchronizes AI coding skills across multiple tools, exposing skill discovery and retrieval via list_skills and read_skill.

Enables MCP clients to infer and resolve skills from text, normalize skill names, perform semantic taxonomy searches, and inspect lifecycle governance.

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

A self-hostable semantic skill registry for AI agents, providing searchable, versioned, and verified skills over a single MCP endpoint with per-agent private vaults and trust tiers.

Enables persistent skill management over the Model Context Protocol, allowing agents to use, write, list, and migrate skills backed by directory, Git, or S3 stores.

A graph-based MCP server that discovers, resolves dependencies, and installs the minimal set of Claude Code components—including skills, agents, and commands—tailored to specific tasks.

Enables AI agents to semantically search and retrieve relevant skills from a local Markdown skill database, reducing context waste by loading only needed skills through tiered detail levels and tool calls.

A visual web interface and MCP server for managing Claude MCP Skills, enabling users to create, edit, browse, and load skill sets through a browser UI or directly from Claude Desktop.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

MCP server that provides access to over 100 development skills for frontend, backend, integration, design, devops, and process categories via Claude Code and other MCP clients.

Enables all IDEs to access Claude Code Skills capabilities with skill discovery, search, and management tools.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

A hierarchical MCP server for managing skill definitions with a browsable tree structure and full-text search. It allows AI agents to efficiently discover and use skills without consuming context tokens.

Enables AI agents to search, browse, install, and manage a large library of skills via only 7 MCP tools, with skills stored locally and loaded on demand to minimize context overhead.

Routes SKILL.md libraries to any MCP client, enabling task matching and skill loading with embedding-based scoring, keyword fallback, and context-window discipline.

Manages a Neo4j knowledge graph of reusable Python functions, documentation, and environment variables, enabling dynamic script composition and execution with automatic dependency management and secret protection.

Enables AI agents and humans to collaboratively plan and manage tasks with a shared kanban and dependency graph, all stored locally.