documentation-server

Documentation Server — REST API Skill

Overview

This server provides a local-first knowledge base with semantic search, parent-child chunking, and an embedded vector database (Orama). Every operation available through the MCP protocol is also accessible via a REST API on http://127.0.0.1:3080/api/.

Calling the REST API directly (with curl or your agent's HTTP tool) is more token-efficient than loading MCP tool schemas — only the response JSON enters context, not the tool definitions.

When to Use

• You need to add, retrieve, search, or delete documents in the knowledge base
• You want semantic search (vector similarity) across one or all documents
• You need to retrieve context windows around matched chunks for richer LLM context
• You need to manage uploads: list files, process them into documents, or get the uploads path
• You want the web UI to browse documents visually, upload files via drag-and-drop, or explore search results interactively
• Context token budget is tight and you want to avoid MCP tool schema overhead

When NOT to use: If the server isn't running and you cannot start it (no npx/Node.js available), fall back to another documentation strategy.

Web Interface

The server includes a full-featured graphical web interface at http://127.0.0.1:3080 that runs automatically alongside the REST API. Use it for:

• Dashboard — overview of all documents and statistics
• Documents — browse, view, and delete documents visually
• Add Document — create documents with title, content, and metadata
• Search — semantic search across all or within a specific document
• AI Search — Gemini-powered analysis (if GEMINI_API_KEY is set)
• Upload Files — drag-and-drop .txt, .md, or .pdf files
• Context Window — explore chunks around a specific index interactively

The REST API is for programmatic access; the web UI is for visual exploration and one-off operations.

Server Lifecycle