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"Developing a Bulk Email System" matching MCP servers:

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    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.
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    A lightweight Model Context Protocol (MCP) server that enables your LLM to validate email addresses. This tool checks email format, domain validity, and deliverability using the AbstractAPI Email Validation API. Perfect for integrating email validation into AI applications like Claude Desktop.
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    Create disposable email inboxes, extract OTP codes in 15 languages, and receive webhooks — all from your AI agent. One call: create inbox → wait for email → get the verification code. Supports 7 domains, email forwarding, and HMAC-signed webhooks with OTP included in payload. Free tier available.
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    MIT
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    A simple MCP server that enables users to send emails using Resend's API, integrating with tools like Cursor and Claude Desktop for seamless email composition and delivery.
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    MIT
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    A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.
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    An MCP service that enables AI to fully manage email accounts, supporting sending emails with attachments and multiple recipients across various email providers.
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    MIT
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    A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.
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    This read-only MCP Server allows you to connect to Email data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp
    Last updated
    MIT
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    A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.
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    107
    MIT
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    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.
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    117
    MIT
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    Creates a local MCP runtime for design-system repositories, enabling AI coding agents to look up and use real components, icons, and tokens instead of guessing.
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    45
    MIT
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    A production-ready template for developing MCP servers with Python and FastMCP, including example tools like a multiply calculator and code review prompt generator.
    Last updated
    Apache 2.0