An advanced MCP server implementing diagrammatic reasoning with memory-augmented spatial exploration, enabling structured chain-of-thought reasoning through visual reasoning spaces.
A locally-running Python REPL server that integrates with Claude Desktop through the Model Context Protocol, offering shell bridge, streaming, and operational memory features for secure code experimentation and system automation.
An MCP server that transforms text into knowledge graphs and autonomously generates insights by combining Montague Grammar with Zettelkasten methodology.
An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.
A Model Context Protocol (MCP) server that enables Claude to use Monte Carlo Tree Search algorithms for deep, explorative analysis of topics, questions, or text inputs.
A meta-MCP server that helps users create new MCP servers through AI guidance, templates, and streamlined workflows, transforming ideas into production-ready implementations with minimal effort.
Provides structured behavioral analysis grounded in Panksepp's affective neuroscience and pattern matching to understand human intent and behavior through primary emotional systems and transition dynamics.
Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.
A Model Context Protocol server implementing the Random Tree Model for encoding, compressing, and recalling narrative information across different levels of abstraction with configurable cognitive parameters.
Enables creating, manipulating, and managing Mermaid diagrams with automatic saving and multi-format conversion from JSON, CSV, Python, Markdown, and plain text.
MCP-Logic is a server that provides AI systems with automated reasoning capabilities, enabling logical theorem proving and model verification using Prover9/Mace4 through a clean MCP interface.
Provides advanced code structure and semantic analysis through Abstract Syntax Trees (AST) and Abstract Semantic Graphs (ASG) across multiple programming languages. It enables tasks like incremental parsing, complexity analysis, and AST diffing to help models understand and navigate codebases.
A self-improving coding agent MCP server that enables code execution, semantic memory, and reusable skills via sub-agents, turning your AI client into a meta-operating system.
A Model Context Protocol server that encodes text, PDFs, and other content into video memory format, enabling efficient semantic search and chat interactions with the encoded knowledge base.
MCP-RoCQ integrates with the Coq proof assistant to enable automated dependent type checking, inductive type definitions, and property proving through XML protocol communication.
Enables fast, on-device machine learning with production-grade persistence through the Model Context Protocol. It allows instant training of text classifiers using Extreme Learning Machines, with SurrealDB-backed persistence and monitoring.
Enables philosophical reasoning and concept analysis through NARS non-axiomatic logic integration, supporting multi-perspective synthesis, epistemic uncertainty tracking, and contextual semantic exploration with built-in truth maintenance.