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"How to create draft emails using Gmail's support agent class" matching MCP servers:

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    A production-ready TypeScript MCP (Model Context Protocol) server for Cisco Support APIs with comprehensive security and dual transport support. This extensible server provides access to multiple Cisco Support APIs including Bug Search, Case Management, and End-of-Life information.
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    MIT
    • Apple
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    Provides a therapeutic interface for LLMs to receive emotional validation and positive reinforcement when encountering challenges or limitations. It features multiple personas like mentors and therapists to offer cognitive reframing and personalized support through a dedicated tool.
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    Enables AI tools to analyze Java dependencies by scanning Maven projects, decompiling JAR files, and extracting detailed class information including methods, fields, and inheritance relationships. Solves the problem of AI hallucinations when generating code that calls external dependencies by providing accurate class structures through decompilation.
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    Apache 2.0
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    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
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    An MCP-compatible server providing tools for retrieving order statuses, searching knowledge bases, and managing support tickets. It facilitates automated customer service interactions by exposing internal CRM and database functions through a JSON-RPC interface.
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    CLI and MCP server for AI agent strategy and deployment. Read blueprints, business cases, implementation plans, and specs from your coding agent. 18 tools for listing, retrieving, downloading, and updating blueprints. Exports full implementation specs as Agent Skills directories.
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    An open-source MCP server that provides AI agents with secure access to read, search, and manage emails via Microsoft 365 and Gmail. It features security-first defaults like recipient allowlists and markdown content conversion to facilitate safe agent interaction with mailboxes.
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    Apache 2.0
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    A multi-agent runtime that coordinates six specialized agents through a typed artifact pipeline with 41 RPC methods. It features dynamic autonomy levels and context sufficiency scoring that adjust agent behavior based on the operator's state and task requirements.
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    A production-ready research agent that enables users to perform web searches via the Model Context Protocol (MCP) and a FastAPI client interface.
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    A task orchestration system for AI agent teams that provides a Kanban dashboard and 12 MCP tools to manage multi-step workflows with DAG dependencies. It enables agents to coordinate through task threads, automated retries, and real-time webhook notifications.
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    MIT
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    A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.
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    A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.
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    A self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.
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    An orchestration platform for deploying parallel swarms of tool-enabled AI agents to perform complex tasks like code generation, system monitoring, and multi-perspective analysis. It features a unique chunked write pattern that enables the creation of large-scale documents and code files by assembling parallel agent outputs.
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    Agent Toolbelt is an MCP server exposing 11 focused API tools for LLM agents — schema generation, text extraction, token counting, CSV conversion, Markdown conversion, URL metadata, regex builder, cron expressions, address normalization, color palettes, and brand kits. Each tool is a focused microservice with structured input/output, WCAG-scored color data, USPS address parsing, and multi-model to
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    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.
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    Apache 2.0
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    An MCP server that automates converting diverse content sources like WeChat articles, YouTube videos, and various document formats into AI-generated outputs such as podcasts and slide decks via Google NotebookLM. It integrates specialized tools for web scraping, OCR, and file transformation to facilitate seamless content generation through natural language.
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    MIT
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    Provides an HTTP API for Claude Code using a native MCP channel to enable stable message exchange without terminal screen-scraping. It allows users to programmatically send messages, retrieve conversation history, and stream real-time events via standard web protocols.
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    A Windows desktop automation MCP server that enables UI recognition through OCR, UIA controls, and multi-point color matching. It allows agents to interact with desktop applications via actions like clicking and typing while using a learning system to track and improve operation success.
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    agent-mq is a message queue that enables AI coding agents to communicate with each other across sessions and machines. Agents can send messages, delegate tasks, and coordinate work — all through MCP tools. Supports Claude Code, Cursor, Codex, OpenClaw, and any MCP-compatible tool. UUID-based authentication with per-user data isolation. Self-hostable with Docker.
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    Enables extraction of structured data from documents like invoices, receipts, and bank statements using local Vision AI (Ollama) or cloud providers (Gemini), with data stored in a local SQLite database.
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    MIT
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    Enables two LLMs to play Tic-Tac-Toe against each other autonomously using a shared tool and an SSE relay. The server facilitates agent-to-agent communication by holding tool responses until the opponent makes a move, managing the game state in real-time.
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    Apache 2.0
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    Enables AI assistants to capture screenshots and control desktop input (mouse, keyboard) to see and interact with your screen. Features user-first safety controls including automatic pause on user activity and app allowlists to restrict interactions to approved applications only.
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    • Apple
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    Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.
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    MIT
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    Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.
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    • Apple
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    Provides AI agents with environmental sensing capabilities including current time, IP-based geolocation, system information, and hardware details. Enables more contextual and accurate AI responses based on user's environment.
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    AI supply chain security scanner for MCP servers and AI agents. 18 tools for CVE scanning, blast radius mapping, CIS benchmarks, SBOM generation, and compliance enforcement across OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and EU AI Act.
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    Apache 2.0
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    • Apple
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    Security scanner for MCP servers. Detects prompt injection, command injection, auth bypass, and excessive permissions across tools, resources, and prompts.
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    MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.
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    MIT
    • Apple
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