DocSync: Agentic Documentation Infrastructure

Turn static documentation into live, agent-readable knowledge. Synchronize, Validate, and Enforce documentation quality using LLMs.

🇧🇷 Português | 🇺🇸 English

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⚡ The Problem

In modern software development, documentation rots faster than code. Developers hate writing it, and AI Agents hallucinate when reading outdated files.

🛡️ The Solution: DocSync

DocSync is not just a linter. It is an Agentic Infrastructure Tool that treats your documentation as a living database. It sits between your codebase and your LLMs, ensuring that every Markdown file is accurate, up-to-date, and semantically structured for retrieval.

"Don't let your Agent read garbage. Feed it DocSync."

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🔥 Key Capabilities

🔌 1. Native MCP Server (Model Context Protocol)

DocSync exposes your entire documentation knowledge base as a structured MCP Server.

• For Claude/Cursor: Connect DocSync to your assistant. It can now "read", "search", and "patch" your docs autonomously.
• No API Gluing: It just works with any MCP-compliant client.

🧠 2. AI-Driven Semantic Validation

Forget regex. DocSync uses LLMs (OpenAI, Anthropic, Gemini) to understand the content of your docs.

• Does this README match what main.py actually does?
• Is the tone consistent across all 50 files?
• Are these installation steps actually executable?

🔄 3. Multi-Provider Intelligence

Agnostic by design. Swap brains on the fly:

• --provider openai (GPT-4o for deep logic)
• --provider anthropic (Claude 3.5 Sonnet for huge context windows)
• --provider gemini (Gemini Pro for speed)

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🚀 Quick Start (Production Ready)

Installation

pip install docsync

1-Click Optimization

Improve your README instantly using your preferred LLM:

export OPENAI_API_KEY="sk-..."
docsync improve README.md --instruction "Make it sound enterprise-ready"

Launch MCP Agent

Turn your folder into a knowledge server:

### Launch MCP Agent
Turn your folder into a knowledge server:
```bash
docsync serve --port 8000

🛠️ Automation (Taskfile)

We use go-task to standardize development commands:

task install   # Install dependencies
task test      # Run tests
task lint      # Check code quality
task clean     # Remove cache
task serve     # Start MCP Server

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🏗️ Architecture & Design

DocSync is built with Resilience and Extensibility in mind.

• Core: Python 3.9+ with strict typing (MyPy).
• Interface: Rich CLI for humans, JSON-RPC for Agents.
• Pattern: Adapter Pattern for LLMs (easy to add Llama 3 or Mistral).

graph LR
    A[Human Dev] -->|CLI Commands| B[DocSync Core]
    C[AI Agent / IDE] -->|MCP Protocol| B
    B -->|Read/Write| D[Markdown Files]
    B -->|Analyze| E[LLM Provider API]

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💼 Enterprise Use Cases

Persona	Benefit
CTOs	Ensure compliance and documentation standards across 100+ repos.
DevOps	Auto-generate changelogs and deployment guides during CI/CD.
Solo Devs	Have a "Documentation Co-pilot" that writes the boring stuff for you.

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🤝 Contributing

We are building the standard for AI-Augmented Documentation. Contributions are welcome for:

• New MCP Tools
• Additional LLM Providers (Ollama, Groq)
• Integrations (Notion, Confluence)

🛣️ Future Roadmap

• Performance Core: Research migration to Go (Golang) for instant CLI execution (< 10ms).
• Cloud Sync: Direct integration with Confluence/Notion APIs.

See CONTRIBUTING.md to join the swarm.

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Built by SH1W4 // Symbeon Labs