Projects sharing features with Eechat

Anthropic's terminal-native AI coding agent.

DocsGPT is a retrieval-augmented generation platform and private knowledge base used to build AI agents that perform grounded search and analysis. It functions as a multi-model AI orchestrator and enterprise agent builder, allowing for the integration of various local and cloud language models to customize reasoning and text generation. The project provides a visual environment for developing automated assistants using conditional logic and third-party API connectivity. It enables the creation of private AI agents capable of performing enterprise search and detailed document analysis using pr

AstrBot is an orchestration framework designed for building and managing autonomous agents that integrate multimodal artificial intelligence with secure, isolated execution environments. It serves as a platform for coordinating complex agentic workflows, allowing users to connect diverse language, speech, and vision models while maintaining personalized agent personas and domain-specific knowledge bases. The platform distinguishes itself through a modular plugin architecture and a centralized visual dashboard, which together enable users to extend agent capabilities and manage operational set

Continue is an automated code review platform that integrates AI agents directly into the software development lifecycle. By executing custom validation rules against pull request diffs, it provides immediate feedback through repository status checks, allowing teams to enforce quality, security, and documentation standards before manual review begins. The system distinguishes itself through a file-based configuration model where validation logic is defined in version-controlled markdown files. These files act as system prompts that guide autonomous agents in evaluating code changes. This appr

ChatMCP is an AI chat client implementing the Model Context Protocol (MCP).

Shinkai is a two click install App that allows you to create Local AI agents in 5 minutes or less using a simple UI. Supports: MCPs, Remote and Local AI, Crypto and Payments.

Enables cloud-based AI services to access local Stdio based MCP servers via HTTP requests

The Simple Agent Development Kit.

Genkit is an open-source framework for building AI-powered applications. It provides a unified interface for connecting to hundreds of generative AI models from multiple providers, enabling text, image, audio, and video generation through a single API. The framework structures multi-step AI interactions—including chat, retrieval-augmented generation, tool use, and agentic workflows—as composable, traceable flows with built-in streaming and state management. The framework distinguishes itself through a comprehensive developer toolkit that includes a command-line interface and a local developer

ZhihuDaily with Swift language

🦁 AI chat & search summaries in Brave Search, powered by the latest LLMs

🐤 AI chat & search summaries in DuckDuckGo, powered by the latest LLMs

This project is a cross-platform desktop application that wraps web-based interfaces into a standalone, native container. By utilizing a webview-based rendering engine, it allows users to access web services as local applications on Windows, macOS, and Linux without requiring a full browser installation. The application is built on a memory-safe backend that manages system-level tasks and facilitates secure communication between the web frontend and the native operating system. This architecture enables features such as system-tray integration for background execution and quick access, provid

This platform serves as a comprehensive environment for managing private language models, document knowledge bases, and automated agent workflows within secure local infrastructure. It functions as a document-aware workspace that enables users to ingest diverse file formats into searchable repositories, ensuring that all data processing and model inference remain within private, local environments to maintain data sovereignty. The system distinguishes itself through a modular agentic engine that allows for the definition of custom skills and external tool execution. By utilizing a multi-model

This project is an AI assistant for Visual Studio Code that utilizes a large language model to generate code and answer programming queries. It functions as a code generator and assistant, enabling the insertion of AI-generated snippets directly into active source files and providing a conversational interface via a side panel chat. The extension facilitates structural refactoring, optimization, and debugging of selected code blocks through natural language prompts. It also generates natural language explanations and technical documentation for complex code segments without requiring the user

AI as Workspace - An elegant AI chat client. Full-featured, lightweight. Support multiple workspaces, plugin system, cross-platform, local first real-time cloud sync, Artifacts, MCP | 更好的 AI 客户端

MCP Server & Config Manager for 14 AI Clients — Cursor, VS Code, Claude Code, Gemini CLI, Windsurf, Zed, TRAE, Kiro, JetBrains & more. 8500+ servers, 4400+ skills.

A simple REST API and CLI client to interact with Model Context Protocol (MCP) servers.

An MCP client for Neovim that seamlessly integrates MCP servers into your editing workflow with an intuitive interface for managing, testing, and using MCP servers with your favorite chat plugins.

PyChatGPT is a Python library for sending prompts to language model APIs and receiving generated text responses programmatically. It serves as an API client that integrates language model capabilities into Python applications. The project includes an automated authenticator to retrieve and refresh access tokens without requiring a web browser. It also features a proxy-enabled network client that routes API requests through proxy servers to bypass network restrictions and manage rate limits. To maintain continuity, the library provides conversation state management that tracks chat history an

A middleware to provide an openAI compatible endpoint that can call MCP tools

Magg: The MCP Aggregator

This project is an Android application that integrates OpenAI language models to provide real-time conversational AI experiences. It functions as a native mobile client, enabling users to send queries to remote language services and view the resulting text responses within an interactive chat interface. The application utilizes a declarative user interface framework to build dynamic messaging layouts and manage conversation states. It employs a component-based architecture that separates UI logic from network communication, ensuring that messaging components remain modular and decoupled from

Unofficial open source Chat AI desktop app for mac, windows, and linux menubar using tauri & rust.

This project is a Python framework for building autonomous AI agents capable of executing independent tasks through goal-oriented instructions. It provides a library of tools for managing system operations and processing multimodal data. The framework features a sandboxed system execution environment that restricts shell commands and file access to protect the host system. It also includes an automated OCR text extraction pipeline for converting printed or handwritten text from images and documents into digital formats. Connectivity is handled through a modular tool integration system and a