Generate standardized LLMs.txt files for websites to define how large language models should interact with web content, providing clear usage guidelines.
Extract text from specific PDF pages or entire documents. Define start and end pages for targeted extraction, or retrieve all text efficiently. Returns text as strings or page-numbered dictionaries.
Bridge the gap between design and code. Send pixel-perfect website components directly to Cursor or Claude Code using Model Context Protocol (MCP). No more screenshots or descriptions needed.
Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.
Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.