"Ways to Improve Thinking Skills" matching MCP servers:

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI agents to perform dynamic and reflective problem-solving through a chain of thoughts, allowing them to break down complex problems, revise past thoughts, and explore logic branches before reaching a conclusion.

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

Enables serving a directory of Agent Skills to MCP clients, listing available skills, delivering their instructions and bundled files, and running only the scripts each skill explicitly declares under strict execution limits.

MCP server that serves agent skills (SKILL.md bundles) to any MCP client, exposing them via tools and resources for tool-oriented and resource-aware clients.

Provides a sequentialthinking tool for dynamic, reflective problem-solving via chain-of-thought reasoning. Supports local Stdio and remote SSE deployment on Google Cloud Run.

MCP server that enables AI programming tools to search, read, and use a remote library of 180+ professional development skills, with incremental caching and network acceleration for fast access.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

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

Connects 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.

Enables discovery and installation of agent skills from curated GitHub repositories, allowing users to search large collections and inspect skill contents directly. It supports downloading skills locally and provides grounded scaffolds for creating new skills based on existing patterns.

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 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.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

Integrates with the skills.sh ecosystem to allow AI coding agents to discover, install, and manage reusable instruction sets. It enables autonomous agents to extend their capabilities with structured skill discovery and full lifecycle management through the Model Context Protocol.

Provides 634+ curated production-ready AI skills for any MCP-compatible client, covering areas like security, frontend, backend, infrastructure, AI/ML, and architecture. Enables AI agents to access best practices, patterns, and solutions across multiple domains.

An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.