#thinking

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

Stops AI from writing duplicate code. Forces Claude/Cursor/Windsurf to analyze existing code first, get approval on plans, then execute step-by-step. Engineering gates ensure no hallucinations or breaking changes.

An enhanced version of the original mcp-sequentialthinking-tools by Scott Spence. This enhanced version significantly improves the original framework with improved utilization of branching, revisiting, and thought revision. Thoughts are much more dynamic and intentional, spread out throughout the conversation at the correct time. There is also caching for tools and thoughts, session continuation and context management, and a bunch of other improvements.

Raycast Extension that acts as an MCP client for the Thinking Partner MCP server

"Tianji" is a powerful thinking model MCP server that integrates hundreds of thinking models, frameworks, and methodologies to help users think more systematically and comprehensively about problems. Through the MCP (Model Context Protocol) interface, AI assistants can access these thinking tools and seamlessly apply structured thinking methods to conversations. The name "Tianji" originates from the ancient Chinese saying "Heaven's secrets must not be revealed," implying that it helps users uncover deeper patterns of thinking and wisdom.

"Tianji" is a powerful thinking model MCP server that integrates hundreds of thinking models, frameworks, and methodologies to help users think more systematically and comprehensively about problems. Through the MCP (Model Context Protocol) interface, AI assistants can access these thinking tools and seamlessly apply structured thinking methods to conversations. The name "Tianji" originates from the ancient Chinese saying "Heaven's secrets must not be revealed," implying that it helps users uncover deeper patterns of thinking and wisdom.

Thinking Models MCP Server is a Model Context Protocol (MCP) based service for querying thinking models. It provides a comprehensive collection of thinking model data, including model definitions, purposes, categories, popular science teaching content, usage notes, and more. This service enables users to easily access and manage various thinking model resources.

The Chroma MCP Server allows you to connect AI applications with Chroma through the Model Context Protocol. Beyond standard MCP interactions, this implementation emphasizes creating a persistent, automatically updated "Second Brain" for development by integrating: Automated Codebase Indexing: Tools and configurations (like Git hooks calling a dedicated chroma-mcp-client) enable automatic indexing of code changes into a designated Chroma collection. Automated Chat Logging: IDE rules (like auto_log_chat for Cursor) facilitate automatic summarization and logging of AI chat interactions into a separate Chroma collection. Working Memory Tools: Specialized MCP commands for capturing and retrieving structured thoughts and development context.

An advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.

A powerful server providing advanced thinking tools via the Model Context Protocol (MCP) to enhance the reasoning, planning, and iterative refinement capabilities of AI agents like Cline.

Taking the sequential thinking mcp server and prodding it onwards.