"A specific URL to visit" matching MCP servers:

A custom MCP protocol service that enhances AI models by providing multilingual translation capabilities and resource management, allowing for automatic text extraction and translation through external APIs.

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.

Enables MCP/AI clients to read project state and execute protected PCB operations in EasyEDA Pro via a local Bridge and official extension APIs.

Provides URL parsing and analysis tools, including component parsing, deterministic hash generation, heuristic safety checks, and metadata extraction, all without external HTTP requests.

一个基于Model Context Protocol的SQLite数据库查询服务，为AI应用提供标准化的数据库访问、安全的SQL查询执行以及表结构预览功能。

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.

Enables MCP clients to securely query databases, list tables, inspect table schemas, and test connections across Oracle, SQL Server, MySQL, PostgreSQL, and SQLite using read-only SQL tools.

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

Read-only Python MCP server for TA-Lib indicator discovery and computation.

Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.

An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

An MCP (Model Context Protocol) server for handling GitHub URLs with validation and parsing capabilities. This server provides tools to convert between GitHub repository information and URLs, with intelligent validation to distinguish between public repositories, private repositories, and non-exist

Provides project-specific guides and instructions by selecting modules based on a project profile, enabling developers to get contextual instructions for their tech stack and architecture.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

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

Extracts SVG icons from Figma and generates React TSX icon components automatically, enabling AI assistants like GitHub Copilot and Claude to manage icon workflows.

mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna