"How to login and extract information from my B2B website" matching MCP servers:

It enables AI agents to call a small set of reliable, permission-aware tools generated from an existing website through the Model Context Protocol, without rebuilding the site.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

MCP server for Averra Extract — lets AI agents like Claude, Cursor, and ChatGPT convert any webpage into clean, LLM-ready Markdown.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

A fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Enables an AI agent to pack a local folder and deploy it as a live static website at a public URL, with no account required for the first publish. Also supports checking site activation, listing existing sites with their status and views, and recovering access to a site whose key was lost.

An MCP server for automated website generation that transforms Excel spreadsheets and structured data into responsive portfolios, catalogs, and directories. It enables users to create complete websites, add pages, and generate components through natural language and template-based integration.

A template MCP server that provides a basic structure and configuration for building Model Context Protocol servers. Includes Docker support, environment configuration, and examples for both STDIO and SSE transport modes.

This server performs a comprehensive analysis of a website by fetching its HTML and scoring it across five categories: performance, SEO, design, functionality, and technology. It enables users to identify technical strengths and weaknesses in a webpage's structure and health.

Turns local Codex session transcripts into a searchable memory that MCP-compatible coding agents can query to retrieve relevant past sessions or exact commands and fixes.

A starter TypeScript template for building MCP and ChatGPT Apps using the Skybridge framework, enabling rapid development and deployment of MCP servers.

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.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.

Enables Codex to trigger an animated hand on your desktop that delivers playful cartoon slaps when mistakes are detected, with severity-based slap counts, while the agent continues working.

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.

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

Tell your AI agent what you want a model to do. It searches Hugging Face for each part of the job and tells you which parts already exist there: which are an exact fit, which to fine-tune, which to train, and which are just code. Every model it names is real, current, and sized for your hardware.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

A TypeScript MCP server boilerplate that provides example tools (calculator, greet) and resources (system info) to kickstart custom MCP server development.

An MCP server that enables AI to interact with the private 'my-design' React component library and design tokens for UI generation and technical support. It provides tools for component searching, API documentation retrieval, and migration guidance based on specific internal design specifications.

Enables MCP-capable IDEs to search 8,214 design-system components, retrieve exact source bundles and semantic tokens, and follow a copy-first handoff workflow with composition validation.

MCP server that exposes code review tasks from the Fix My Comments VS Code extension to AI agents, enabling them to list, retrieve, reply to, and update task statuses.

Provides a single MCP tool that returns the current time for a requested timezone, connectable to Claude Code and Claude desktop over stdio or Streamable HTTP.

An MCP server providing comprehensive HubSpot CMS development documentation, enabling users to get contextual information about building HubSpot websites through natural language.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.