MCP-Docusaurus

# 🧠 MCP Docusaurus Toolkit A modular Content Management Platform (MCP) to manage, embed, and search Docusaurus documentation using **FastAPI**, self-hosted embeddings, and **PostgreSQL + pgvector**. --- ## 🚀 Features - 📁 Auto-generate site map from Docusaurus docs - 📝 Create, update, and continue editing Markdown docs - 🧠 Vectorize content using pluggable embedding models - 🔍 Perform RAG-style semantic search across the docs - 🧾 Track incomplete docs with watermarks - 🔄 Sync external edits into the vector database - 🎨 Apply style/theme transformations to docs - 🧪 Built-in tool decorators for AI agent control --- ## 📂 Project Structure ``` . ├── app/ │ ├── main.py # FastAPI entrypoint with FastMCP + tools │ ├── routes/ # Modular endpoints (docs, search, styles, site\_map) │ ├── embeddings/ # Embedding model configuration + logic │ ├── database.py # PostgreSQL + pgvector connection logic │ ├── models/ # DB + Pydantic models for documents │ ├─── utils/ # Sync tools, helpers │ └── docs/ # Full editable Docusaurus source (used in dev mode) │ ├── data/ │ ├── docusaurus/ # Runtime-synced Markdown docs │ └── embeddings/ # Persisted vector embeddings │ ├── Dockerfile # Multi-stage (Node + Python) ├── docker-compose.yml # Services: FastAPI, Docusaurus Dev, Postgres ├── requirements.txt └── README.md ```` --- ## 🐳 Getting Started (Docker) ```bash # 1. Clone this repository git clone https://github.com/your-org/mcp-docusaurus.git cd mcp-docusaurus # 2. Launch services docker compose up --build ```` * 🌐 MCP API available at: [http://localhost:8000](http://localhost:8000) * 📚 Docusaurus live dev server: [http://localhost:3000](http://localhost:3000) --- ## 🧰 Tooling Overview (MCP API) ### ➕ Create a New Document ```http POST /tool/create_document ``` ```json { "path": "guides/new-feature.md", "title": "New Feature", "content": "## Work in Progress..." } ``` --- ### ✍️ Update Existing Document ```http POST /tool/update_docs ``` ```json { "path": "guides/new-feature.md", "line_begin": 10, "line_end": 15, "new_text": "Updated explanation here." } ``` --- ### 🧠 Vector Search (RAG-Style) ```http POST /tool/search_docs ``` ```json { "query": "How to authenticate a plugin?" } ``` --- ### 🎨 Apply CSS or Theme Style ```http POST /tool/apply_style ``` ```json { "style_id": "dark-theme", "content": "..." } ``` --- ## 🔌 Embedding Model Support Pluggable embedding model backend with simple config. ### ✅ Local (Default) * `sentence-transformers/all-MiniLM-L6-v2` ### 🌐 Optional Remote Support * OpenAI Embeddings (requires API key) --- ## ⚙️ Environment Configuration Use `.env` file or Docker `environment:` block: ```env PG_HOST=postgres PG_USER=postgres PG_PASSWORD=postgres PG_DATABASE=vector_db EMBEDDING_MODEL=local ``` --- ## 🔐 Security * 🔒 Tool routes are gated with `@tool` decorators * ✏️ Document writes are verified before embedding * 🔑 Optional OAuth2 / API Token guardrails available --- ## 📘 Docusaurus Notes * The `doc/` directory holds the full Docusaurus source (used for live editing). * The `data/docusaurus/` directory contains generated Markdown synced with the vector database. --- ## 📊 Metrics & Health * `GET /tool/health_check` – Check if the API is alive * `GET /tool/metrics` – Prometheus/Grafana-compatible stats --- ## 📝 License MIT License ©️ \[guidry company]