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    A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.
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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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    MIT
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    A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.
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    Apache 2.0
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    Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.
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    MIT
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    MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution
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    21
    MIT
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    A lightweight and fast MCP server that enables AI agents to efficiently discover and execute tools through progressive disclosure, minimizing context consumption while supporting safe code execution in external environments.
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    An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.
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    MIT
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    A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.
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    MIT
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    Enables Claude Code to perform programmatic tool calling by executing Python scripts that interact with multiple MCP servers in a single round-trip. This reduces latency and token consumption by keeping intermediate tool results within the local Python runtime instead of the conversation context.
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    MIT
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    Enables AI agents to debug embedded systems by providing a comprehensive interface for GDB operations across multiple architectures like ARM and x86. It supports remote debugging via gdbserver or QEMU, allowing for detailed inspection of memory, registers, stack frames, and variables.
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    Enables automation of Google Jules AI coding assistant through task creation, code review automation, repository management, and AI-powered development workflows. Supports multiple session modes including cloud deployment with persistent authentication.
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    A local MCP server that provides a safe plan-and-execute workflow for AI coding assistants, storing plans and tasks, and executing agent commands with an allow-list for security.
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    MIT
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    MCP server for managing Git operations on local repositories, allowing users to list repositories, get and create tags, list commits, push tags, and refresh repositories through a standardized interface.
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