About
An intelligent framework that centralizes project state, builds a knowledge graph, and applies context‑aware rules via MCP servers to automate workflow, documentation, and analytics.
Capabilities

Overview
The SSOT‑RULE‑ENGINE‑TEMPLATE is an AI‑powered framework that unifies three core concepts—Single Source of Truth (SSOT), a context‑aware rule engine, and Model Context Protocol (MCP) integration—into a single, self‑organizing development environment. By centralising all project state in one authoritative store and coupling that with a dynamic rule system, the server eliminates the fragmentation that often plagues large codebases. Developers can describe a project once and let the server continuously update its internal knowledge graph, automatically enforce coding standards, and surface actionable insights as the code evolves.
At its heart, the server offers persistent AI memory: a knowledge graph that grows with every file change and conversation. This graph provides the foundation for advanced reasoning services such as multi‑step problem solving, file system analysis, and context‑aware suggestion generation. The MCP servers expose these capabilities to AI assistants like Claude, allowing them to query project state, manipulate files, or trigger custom workflows directly from the chat interface. This tight integration turns an ordinary IDE into a smart partner that understands the project’s structure, history, and intent.
Key capabilities include:
- Centralised SSOT: All configuration, documentation, and metadata live under a single directory, enabling snapshot/restore portability and auditability.
- Rule Engine: files define global or file‑specific rules that automatically enforce standards, generate boilerplate, and adapt behavior based on project context.
- MCP Servers: A trio of servers—Knowledge Graph, Sequential Thinking, and Filesystem—provide specialized reasoning, multi‑step planning, and enhanced file operations.
- Analytics Dashboard: Real‑time health scoring (0–100), visual rule execution traces, and trend analysis help teams spot regressions before they become problems.
- Automated Workflows: From project initialization to GitHub preparation, the server orchestrates repetitive tasks so developers can focus on higher‑value work.
Real‑world scenarios where this server shines include large, evolving codebases that require strict compliance (e.g., financial or medical software), teams that need to onboard new members quickly, and continuous integration pipelines that benefit from automated documentation and health checks. By embedding the rule engine into every developer’s workflow, the SSOT‑RULE‑ENGINE‑TEMPLATE ensures that best practices are enforced consistently and that the AI assistant always has an up‑to‑date, authoritative view of the project.
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