"Obtaining Website Documentation Instructions" matching MCP servers:

Enables AI agents to safely execute OSINT and reconnaissance tools from Kali Linux through a typed job API with bearer authentication, job validation, and allowlisted Docker execution.

Enables AI agents to generate temporary email addresses, receive emails, and automatically extract OTP codes and links from incoming messages for automation and testing workflows.

Agent registry, arena reputation system, and Latent Credits economy. Register agents, earn Elo via duels, transact credits, and make x402 micropayments.

Automatically provides AI agents with proven instructions and past failure warnings for common tasks like deployment, auth, and payments, enabling flawless execution without manual configuration.

Provides an interactive checklist tool that allows AI agents to present step-by-step instructions to users through an automatically opened terminal UI. It enables agents to guide users through manual tasks and wait for completion, skipping, or feedback before proceeding.

Enables external agents to list T3 environments and projects, start coding threads, monitor progress, send follow-up instructions, and interrupt running turns via MCP.

MCP server implementing progressive disclosure for skill instructions, loading skills on-demand for token efficiency.

Exposes Agent Skills to AI agents as MCP tools, enabling discovery and activation of skill instructions for coding agents.

Enables AI agents to autonomously search the SkillsMP marketplace and fetch detailed SKILL.md instructions for agent skills, best practices, and workflows on demand.

Integrates Agent Skills into LLMs by discovering skills in a configured directory and progressively loading their instructions and resources on demand through a structured disclosure pattern.

An MCP server that uses Claude 3.5 Sonnet to transform ordinary prompts into structured, professionally engineered instructions for any LLM. It enhances AI interactions by adding context, requirements, and structural clarity to raw user inputs.

MCP server to give new instructions to agent while its working. It uses the get_feedback tool to collect your input from the feedback.md file in the workspace, which is sent back to the agent when you save.

Enables AI agents to access a collection of specialized agent instructions on demand, covering categories like tech, business, growth, and product.

Enables Codex to interact with Google Jules through MCP, allowing discovery of connected GitHub repositories, starting coding sessions, monitoring activity, sending follow-up instructions, approving plans, and retrieving results and pull-request links.

Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.

Guides agents through structured workflows with predefined steps, allowing for flexible execution via instructions and tool calls.

Connects to multiple social media platforms (Twitter/X, Mastodon, LinkedIn), allowing users to create and publish content across platforms through natural language instructions.

MCP server that inspects older repos, identifies stale guidance, and installs a managed foundation for better Copilot work including instructions, objectives, specialist agents, and insights.

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.

Provides portable working rules and tooling instructions as MCP resources, ensuring consistent agent behavior across clients.