"Tools and frameworks for thinking about software development" matching MCP servers:

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

Enables any MCP client to surface twelve structured thinking frameworks for clarifying questions, learning, problem-solving, decision-making, and self-reflection, with fillable slash commands for humans and programmatic retrieval for agents.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

Provides AI systems with structured thinking frameworks and reasoning tools to maintain consistent problem-solving patterns across conversations. Enables multi-step reasoning, decision analysis, and systematic troubleshooting through invocable mental models.

Persistent sequential thinking for MCP clients, stored durably on Cloudflare Workers with support for branching, revision, and history retrieval.

A powerful MCP server that enhances LLMs with advanced sequential thinking capabilities, supporting 19 thinking modes for structured reasoning and complex cognitive tasks.

Provides software development planning tools to help users create implementation plans and manage todo items.

An MCP server for downloading and reading MGX thinking logs, enabling AI agents to fetch and analyze MGX conversation logs programmatically.

Provides comprehensive development tools for FastMCP projects including documentation access, NPM package version management, and TypeScript type definitions retrieval. Enables developers to fetch FastMCP documentation, analyze NPM packages, and access MCP architecture information through natural language.

Enables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.

Enables AI agents to achieve production-ready solutions through iterative refinement and recursive thinking processes. It features token optimization via context compression and session-based tracking to improve problem-solving depth while minimizing cost.

A Model Context Protocol (MCP) server implementation for the Google Gemini language model. This server allows Claude Desktop users to access the powerful reasoning capabilities of Gemini-2.0-flash-thinking-exp-01-21 model.

Provides Dify apps with a secure, app-scoped MCP tool catalog and action gateway for authorized FlowFlox operations, enabling intent-driven planning and fixed operational processes without exposing global credentials.

Provides a tool for dynamic and reflective problem-solving through structured sequential thinking, and automatically stores logs to the Recall network for on-chain persistence.

An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.

A structured problem-solving MCP server that breaks down complex tasks into sequential steps, supports iterative refinement and branching, and helps maintain context and explore alternative reasoning paths.

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

Provides advanced probabilistic decision-making algorithms including MDPs, MCTS, Multi-Armed Bandits, Bayesian Optimization, and Hidden Markov Models to help AI assistants explore alternative solutions and optimize long-term decisions.