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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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    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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    MIT
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    Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.
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    MIT
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    Enable Claude Code, Cursor, or your favorite LLM to interact with Xcode, building your projects the same way you do, and seeing the same errors. Greatly increases productivity when working on iOS, iPadOS, macOS, visionOS, tvOS projects & Swift packages - or any time you might use Xcode.
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    MIT
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    A general-purpose MCP server providing web search, persistent memory storage, and secure code execution capabilities. It enables AI agents to search the web, store and retrieve data, and run Python/JavaScript code in sandboxed environments.
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    MIT
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    A foundational project for quickly developing Model Context Protocol servers using the TypeScript SDK and Zod for schema validation. It features pre-implemented examples for tools like a calculator and greeting service, along with templates for managing dynamic resources.
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    A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.
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    Provides GDB debugging functionality for use with Claude or other AI assistants, allowing users to manage debugging sessions, set breakpoints, examine variables, and execute GDB commands through natural language.
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    MIT
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    A multi-language code analysis server that helps LLMs or humans automatically lint, type-check, and improve code with minimal installation friction, currently supporting Python with plans for other languages.
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    MIT