"Deploying a Website Using BaoTa (BT) Panel" matching MCP servers:

MCP server that fetches and converts website pages into clean markdown for agents, with sitemap-based discovery, disk caching, and polite crawling (robots.txt, rate limiting).

Enables deterministic bilingual website intelligence audits by URL, returning fixed English or Spanish findings without ever contacting the submitted site.

Fast, token-efficient web content extraction tool that converts websites to clean Markdown for AI agents, featuring smart caching, content extraction with Mozilla Readability, and polite crawling capabilities.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables tracking webpage content and price changes over time, including diffs, historical records, and alerts. Supports protected pages with automated browser rendering and anti-bot handling.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables AI agents to scrape, crawl, clean, chunk, and index website content into Azure AI Search for full-text retrieval.

An advanced management platform that integrates FastAPI and React TypeScript, providing a modern user interface with SQLite database and action history tracking.

Fetches and analyzes website content to provide business context to AI agents, designed for Voice AI in GoHighLevel.

Enables Claude to directly manage the Savage in a Suit website through 31 tools for pages, events, members, testimonials, podcast episodes, and site content, with all changes logged.

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

An MCP server that extracts meaningful content from websites and converts HTML to high-quality Markdown, using Mozilla's Readability engine.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.