"A guide to improving cognitive skills and thinking processes" matching MCP servers:

A sophisticated MCP server that provides a multi-dimensional, adaptive reasoning framework for AI assistants, replacing linear reasoning with a graph-based architecture for more nuanced cognitive processes.

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.

Structures debugging processes into a persistent knowledge graph, enabling problem decomposition, hypothesis testing, and reusable solution discovery.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

Enables LLM agents to persist, search, update, forget, summarize, and manage user cognitive memories through MCP tools.

Enables coding agents to pre-screen commands for destructive patterns and credential leaks, arbitrate escalation with a five-factor controller, route tasks by complexity, verify completions, and rerank candidates through MCP tools. Outputs are advisory, with optional probabilistic triage requiring an external JevBridge runtime.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

This is a MCP server that implements an unreasonable thinking system. It helps generate unconventional solutions: Generating unreasonable thoughts that challenge conventional wisdom. Creating branches of thinking in different directions

Provides access to clean code guide documents and enables code quality inspection of external project files based on coding standards and best practices.

Enables agents to reason through a validated 28-layer cognitive substrate, evolve tree-of-thoughts memory across sessions, and communicate with peer agents via A2A tools.

Provides Claude with persistent memory and learning capabilities through 10 automatic agents that capture decisions, errors, solutions, and patterns across conversations. Features an anti-compaction system to prevent context loss and enables infinite conversation continuity.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

A multi-agent system for code rules management using MCP, supporting search, generation, and architectural validation through specialized agents.

A structured, persistent reasoning workspace for AI. 20 tools for thought chains, branching, revision, search, tagging, and SQLite session persistence that survives context window resets and server restarts.

This MCP server enables AI agents to interact with Ripar's decentralized registries on Algorand, offering tools for searching agents, checking reputations, listing jobs, auditing settlements, and composing unsigned transactions for payments.

Enables AI assistants to search a library of over 20,000 open legal skills by keyword, by meaning, or a hybrid of both, filtering by jurisdiction, language, practice area, or tag. It also returns facet counts for the collection and retrieves the full text of any selected skill.

Enables MCP hosts to discover, browse, and load Agent Skills from one or many SKILL.md libraries over the Model Context Protocol, with namespaced libraries, search/list/get tools, progressive disclosure, and a digest-verified pull client for syncing skills to disk.

Open-source skills that empower any AI agent (Claude, Cursor, Codex, Hermes, etc.) to generate end-to-end marketing campaigns — UGC videos, ad videos, product photography and more. From a product photo and a brief it casts AI actors, picks the best models, and edits finished assets of any length with consistent actor and product. It also researches competitors, publishes, and reviews performance.

Builds a dynamic knowledge graph from your notes and uses LLM reasoning to discover blindspots, hidden cross-domain connections, track concept evolution, and spark creative inspiration.

MCP connector for the ok-wiki knowledge base, enabling search, read, create, edit, history, tags, and asset management via natural language.

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.

Provides deterministic parental guidance for children with chronic kidney disease, including food safety checks, lab report interpretation, and nutrient-aware food substitutions based on authoritative guidelines and the Chinese Food Composition Table.

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

A universal MCP server that enables any LLM or AI agent to access expert skills from your local filesystem.

An MCP server that transforms books into agent-callable skill packages, enabling AI agents to use books as guides for evidence, procedures, and tutoring.

Serves a bundled greeting skill over stdio using the MCP Skills extension, letting clients discover the skill's metadata and digest, read its SKILL.md as an ordinary MCP resource, and invoke a greet tool that returns a personalized hello.

Serves any directory of Agent Skills (SKILL.md folders) over MCP, exposing skills/list, skills/get, and skill:// resources so clients can enumerate and retrieve each skill's frontmatter and files. Every returned file comes with a real SHA-256 digest, letting clients verify content rather than merely trust it.

Enables auditing OpenClaw's loaded skills for per-step token cost, shadowed duplicates, broken references, and budget overruns, then produces a measured plan to trim or hide expensive skills and archive unused duplicates.

An MCP server that enhances sequential thinking with Ultra Think methodology, enabling structured, step-by-step reasoning with quality metrics, bias detection, and resource management.