# Multi-language

Gossiphs is a zero-configuration, high-performance general code file relationship analysis tool that supports multiple programming languages. It is based on tree-sitter and git analysis, provides support for Python SDK and MCP protocol, and is convenient for integration with AI.

League of Legends Mock Match Predictor, providing summoner analysis based on historical data and AI-driven 10-phase match simulation, supporting multi-language and performance comparison.

OpenManus is an open-source project that allows users to realize various ideas without an invitation code. It was built by members of the MetaGPT team in 3 hours. It provides a simple implementation that allows users to create their own intelligent agents and supports multiple languages and configurations. The project welcomes suggestions, contributions, and feedback. Future plans include better planning, real-time demonstrations, playback functions, RL fine-tuning models, and comprehensive benchmarking.

A multi-language code comment cleaning service based on the MCP protocol, supporting batch processing of files in multiple programming languages. Developed using TDD to ensure quality.

A collection of multi-language implementations of the MCP Geocoder, providing three different implementation methods in Python and TypeScript, serving as a reference template for developers to create MCP tools.

An MCP date and time formatting service implemented for the Claude desktop application, supporting the generation of multiple date and time formats

A multi-language code dependency analysis service that generates dependency graphs and architectural scores

An MCP server based on TypeScript, which uses Faker.js to provide various fake data generation functions, supporting multiple languages and custom configurations.

VideoLingo is a tool that integrates video translation, localization, and dubbing, aiming to generate Netflix-quality subtitles. It eliminates生硬的机器翻译 and multi-line subtitles while providing high-quality dubbing to achieve cross-language knowledge sharing.

MCP Server MAS Sequential Thinking is a server environment project focused on enhancing the sequential thinking process, providing modular design, scalability, and multi-language support, suitable for education, research, and application development.

The AutoDev MCP example project demonstrates the configuration of Model Context Protocol services implemented in multiple languages

glyph is a code symbol extraction tool based on Tree-sitter. It extracts symbol outlines from the codebase through a declarative query language, provides structured context for LLM programming agents, supports multiple languages, and has configurable levels of detail.

This project provides an MCP server implementation with a waiting function, including TypeScript and Python versions, which can pause for a specified time before responding to requests.

A Google job search MCP server based on SerpAPI, providing multi-language support, flexible search parameters, and smart error handling.

A multi-functional code scanning tool that supports multi-language parsing, definition extraction, and .gitignore filtering, can output results in multiple formats, and provides two running modes: CLI and MCP server.

This is a Spring Boot-based weather service application that provides a REST API for querying current weather information by city name.

A Python service that provides a YouTube video transcription API, supporting REST and MCP interfaces, with multi-language transcription, automatic detection, and audio transcription fallback functions.

A voice call server based on the MCP protocol, integrating Twilio and OpenAI technologies to enable AI assistants to initiate and manage real-time voice calls, supporting multi-language switching and preset scenario templates.

This project provides the function of downloading subtitles from platforms such as YouTube and Bilibili, supports multiple languages, and integrates with the AITransDub MCP service.

This is a demonstration repository created through the GitHub MCP server, showcasing the functions of the MCP server, GitHub API integration, and multi-language support.

MCPLab is a collection project of server-client examples, code snippets, design patterns, and tutorials focused on the Model Context Protocol (MCP), aiming to help developers quickly build MCP-driven applications.