Sdof
Manages persistent memory and context for AI systems through a structured 5-phase optimization workflow.
About
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.
Key Features
- Semantic search with OpenAI embeddings
- 0 GitHub stars
- 5-Phase Optimization Workflow
- Structured Content Types
- Multi-Interface (MCP tools and HTTP API)
- Persistent storage with MongoDB/SQLite and vector indexing
Use Cases
- AI-assisted decision making
- Knowledge management for AI systems
- Optimization of AI workflows
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