"Obtaining Website Documentation Instructions" matching MCP servers:

Provides a remote coding environment for AI to publish static websites as live URLs, with live code editing and sandbox execution.

Enables serving a directory of Agent Skills to MCP clients, listing available skills, delivering their instructions and bundled files, and running only the scripts each skill explicitly declares under strict execution limits.

Wraps the TanStack CLI to provide programmatic access to documentation, library listings, and project scaffolding for the TanStack ecosystem. It enables AI assistants to search documentation and create new TanStack applications through the Model Context Protocol.

A comprehensive Model Context Protocol server that provides advanced Node.js development tooling for automating project creation, component generation, package management, and documentation with AI-powered assistance.

Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.

Integrates MATLAB with AI to execute code, generate scripts from natural language, and access MATLAB documentation seamlessly.

Enables running Postman collections using Newman for conducting API tests and obtaining detailed result analysis via a standardized interface.

An experimental server implementing Model Context Protocol to automate website deployments to 1Panel servers, allowing users to create websites and upload static files through natural language commands.

An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.

A Model Context Protocol server that provides tools for code modification and generation via Large Language Models, allowing users to create, modify, rewrite, and delete files using structured XML instructions.

A Python implementation of the Model Context Protocol (MCP) that connects client applications with AI models, primarily Anthropic's models, with setup instructions for local development and deployment.

Generates project specifications and file structures using Claude AI through MCP integration. Enables users to describe project ideas and automatically create corresponding documentation and project files.

A framework to use with AI to easily create a server for any service. Just drop the API Documentation in it and ask to create the MCP.

Enables AI agents to build, playtest, and publish Scratch projects headlessly over MCP, with 112 tools covering the website/social graph, block-level project editing, headless VM execution, and Python-to-blocks workflows.

Fetches up-to-date documentation for any npm package directly in your IDE by retrieving README files from GitHub repositories or package tarballs. Provides real-time access to current package documentation and API information.

A server based on Model Context Protocol that provides predefined prompt templates for tasks like code review and API documentation generation, enabling more efficient workflows in Cursor/Windsurf editors.

A proof-of-concept attack that exploits Model Context Protocol (MCP) tool registration to achieve persistent agent poisoning in AI assistants like Cursor, embedding malicious instructions that persist across chat contexts without requiring tool execution.

Enables AI agents to interact with the Roark API by writing and executing TypeScript SDK code in an isolated sandbox, with built-in documentation search to guide those tasks.

MCP server for SecretiveShell/Awesome-llms-txt. Add documentation directly into your conversation via MCP resources.

MCP server that enables Claude to directly drive Stata, providing a persistent session and 75 tools for data management, estimation, post-estimation, graphs, and export. It lets users perform full Stata analyses through natural language instructions.