Generate machine-readable permission guidelines for AI models by creating standardized LLMs.txt files that define how large language models should interact with websites.
Generate machine-readable permission guidelines for AI models by creating standardized llms.txt files that define how large language models should interact with websites.
Extract webpage content as Markdown formatted text, tailored for large language models. Supports custom CSS selectors, link inclusion, and length limits via Concurrent Browser MCP.
Generate a standardized llms.txt file for any website to define how AI models should interact with the site, creating machine-readable permission guidelines for large language models.
Fetch Python documentation directly using natural language queries. This tool helps developers quickly access relevant Python documentation by integrating with the Brave Search API.
Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.
An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.
Enables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.