Enables AI development tools to maintain context across chat sessions with automatic branching, progress tracking, and TODO management for different tasks.
An MCP server that provides deterministic math computation (numeric, symbolic, unit, matrix) and hybrid retrieval over study notes/textbooks with citations, helping Claude become a reliable study partner.
Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.
Enables persistent storage and retrieval of decisions, settings, and operational rules across chat sessions, maintaining context continuity and decision consistency for long-term development projects through structured memory management.
MCP server for managing AI prompts with CRUD operations, categorization, and tagging. Enables users to store, organize, and retrieve their favorite prompts efficiently.
A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.
Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).
Self-documenting MCP server enabling AI agents to autonomously create, manage, and query SQLite databases with enforced metadata requirements for discoverability.
Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.
Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.
An automated system that processes raw text through a three-stage pipeline to assess data quality, enhance information, and generate structured knowledge graphs. It provides tools for triple extraction with confidence scoring and creates interactive HTML visualizations of the resulting graph.
A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.
A Python-based system that provides AI-powered code reviews through simulated expert personas like Martin Fowler and Robert C. Martin, using the Model Context Protocol (MCP).
Tracks and manages code changes from Git repositories, generates documentation automatically, and provides AI agents with intelligent access to service documentation through MCP server integration with feature mapping and search capabilities.
Server for managing academic literature with structured note-taking and organization, designed for seamless interaction with Claude. Built with SQLite for simplicity and portability.
Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.
Enables persistent memory and semantic search for development workflows with hierarchical compression. Store and retrieve development knowledge across IDE sessions using natural language queries, circumventing context window limitations.