Manages persistent memory and context for AI systems through a structured 5-phase optimization workflow.
SDOF (Structured Decision Optimization Framework) is a Model Context Protocol (MCP) server designed to provide persistent memory and structured context management for AI systems. It employs a 5-phase optimization workflow encompassing exploration, analysis, implementation, evaluation, and integration. SDOF utilizes vector embeddings (powered by OpenAI) for semantic search and offers schema validation for structured content types, making it suitable for advanced knowledge management and AI workflow optimization. It provides both MCP tool interfaces and an HTTP API for versatile accessibility.
主な機能
01Semantic search with OpenAI embeddings
020 GitHub stars
035-Phase Optimization Workflow
04Structured Content Types
05Multi-Interface (MCP tools and HTTP API)
06Persistent storage with MongoDB/SQLite and vector indexing
