Awesome GitHub RepositoriesMessage Archiving

WildfireChat’s im-server is an open-source instant messaging backend that handles message routing, user management, and group chat for private deployments. It provides a self-hosted messaging platform that can run on private infrastructure without third-party cloud dependencies, supporting enterprise messaging with group management, user directories, and external system integration. The server synchronizes messages and state across mobile, desktop, web, and mini-program clients simultaneously, and supports real-time audio/video calls with group conferencing and live streaming. It includes enc

WechatExporter is a chat backup conversion tool designed to extract WeChat chat records from backups and convert them into human-readable text, HTML, or PDF files for archiving. It functions as a data extraction system that transforms proprietary messaging database backups into standardized document formats. The project includes a template-based document generator that allows users to modify the visual layout and formatting of exported conversation records. It also features an incremental export system that tracks and saves only new messages sent since the previous export to prevent data dupl

OpenWeChat 是一个 Go 语言软件开发工具包（SDK）和 API 包装器，专为将微信消息和账户管理集成到 Go 应用中而设计。它作为机器人框架和消息库，用于处理实时聊天事件及与平台的程序化交互。 该项目提供了一套完整的会话管理系统，包括二维码身份验证和以 JSON 格式持久化会话 Cookie，以在重启后保持访问权限。它通过提供拦截并保留发送者试图撤回的消息的能力，以及对多账户会话管理的支持而脱颖而出。 该库涵盖了广泛的功能领域，包括自动化消息发送和回复逻辑、联系人与群组管理以及用户资料数据检索。它还包含媒体处理工具，例如下载共享文件并通过文件头分析识别内容类型。 该 SDK 实现了基于中间件的消息链式处理系统，并使用基于轮询的事件检测来同步传入数据。

PGMQ 是一个轻量级消息队列系统，作为 PostgreSQL 扩展实现，用于管理异步任务。它充当数据库支持的消息代理，利用 PostgreSQL 进行持久化存储、原子操作和基于通知的投递。 该系统提供了一个兼容 SQS 的队列模型，具有可见性超时和延迟投递功能。它通过组键支持严格的先进先出（FIFO）排序，并支持批量检索，以确保相关任务的顺序处理。 该项目涵盖了完整的消息生命周期，包括生产、通过原子弹出操作进行消费，以及队列清理和生命周期控制等管理功能。它包括通过基于主题的模式进行路由的能力，以及死信队列、消息归档和重试逻辑等可靠性功能。此外还提供了监控工具来跟踪队列长度和吞吐量等操作指标。

This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit