The docs-mcp-server repository contains the server-side code for the documentation management system. It provides functionalities for managing, storing, and retrieving documentation files. Users can upload, update, and delete documents through the server. The server also supports user authentication and authorization to ensure secure access to the documentation system. Additionally, the server includes APIs for integrating with other systems and tools, making it a versatile solution for managing documentation in various projects and organizations.

This project implements a web API that offers a unified interface to Google Gemini and Claude 3. It provides a self-hosted, lightweight, and scalable solution for accessing these AI models through a streaming API. The API supports both Claude and Gemini models, allowing users to interact with them in real-time. The project includes a user-friendly web UI for configuration and documentation, making it easy to get started and explore the capabilities of the API.

Build your own conversation-based search with AI, a simple implementation with Node.js & Vue3. Live Demo Features: * Built-in support for LLM: OpenAI, Google, Lepton, Ollama(Free) * Built-in support for search engine: Bing, Sogou, Google, SearXNG(Free) * Customizable pretty UI interface * Support dark mode * Support mobile display * Support local LLM with Ollama * Support i18n * Support Continue Q&A with contexts.

Zotero MCP seamlessly connects your Zotero research library with AI assistants like ChatGPT and Claude via the Model Context Protocol. It offers AI-powered semantic search, access to library content, PDF annotation extraction, and easy updates. Users can search their library, analyze citations, and get summaries, making it ideal for research tasks. The tool supports multiple embedding models, intelligent search results, and flexible access methods for both local and remote collaboration. With advanced features like semantic search and PDF annotation extraction, Zotero MCP enhances research efficiency and organization.

AiderDesk is a desktop application that enhances coding workflow by leveraging AI capabilities. It offers an intuitive GUI, project management, IDE integration, MCP support, settings management, cost tracking, structured messages, visual file management, model switching, code diff viewer, one-click reverts, and easy sharing. Users can install it by downloading the latest release and running the executable. AiderDesk also supports Python version detection and auto update disabling. It includes features like multiple project management, context file management, model switching, chat mode selection, question answering, cost tracking, MCP server integration, and MCP support for external tools and context. Development setup involves cloning the repository, installing dependencies, running in development mode, and building executables for different platforms. Contributions from the community are welcome following specific guidelines.

Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe supports various features like AI-friendly code extraction, fully local operation without external APIs, fast scanning of large codebases, accurate code structure parsing, re-rankers and NLP methods for better search results, multi-language support, interactive AI chat mode, and flexibility to run as a CLI tool, MCP server, or interactive AI chat.

Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.

LEANN is an innovative vector database that democratizes personal AI, transforming your laptop into a powerful RAG system that can index and search through millions of documents using 97% less storage than traditional solutions without accuracy loss. It achieves this through graph-based selective recomputation and high-degree preserving pruning, computing embeddings on-demand instead of storing them all. LEANN allows semantic search of file system, emails, browser history, chat history, codebase, or external knowledge bases on your laptop with zero cloud costs and complete privacy. It is a drop-in semantic search MCP service fully compatible with Claude Code, enabling intelligent retrieval without changing your workflow.

Gemini Coder is a free 2M context AI coding assistant that allows users to conveniently copy folders and files for chatbots. It provides FIM completions, file refactoring, and AI-suggested changes. The extension is versatile, private, and lightweight, offering unmatched accuracy, speed, and cost in AI assistance. Users have full control over the context and coding conventions included, ensuring high performance and signal to noise ratio. Gemini Coder supports various chatbots and provides quick start guides for chat and FIM completions. It also offers commands for FIM completions, refactoring, applying changes, chat, and context copying. Users can set up custom model providers for API features and contribute to the project through pull requests or discussions. The tool is licensed under the MIT License.

GPT Computer Assistant (GCA) is an open-source framework designed to build vertical AI agents that can automate tasks on Windows, macOS, and Ubuntu systems. It leverages the Model Context Protocol (MCP) and its own modules to mimic human-like actions and achieve advanced capabilities. With GCA, users can empower themselves to accomplish more in less time by automating tasks like updating dependencies, analyzing databases, and configuring cloud security settings.

Orra is a tool for building production-ready multi-agent applications that handle complex real-world interactions. It coordinates tasks across existing stack, agents, and tools run as services using intelligent reasoning. With features like smart pre-evaluated execution plans, domain grounding, durable execution, and automatic service health monitoring, Orra enables users to go fast with tools as services and revert state to handle failures. It provides real-time status tracking and webhook result delivery, making it ideal for developers looking to move beyond simple crews and agents.

ctx is a tool designed to automatically generate organized context files from code files, GitHub repositories, Git commits, web pages, and plain text. It aims to efficiently provide necessary context to AI language models like ChatGPT and Claude, enabling users to streamline code refactoring, multiple iteration development, documentation generation, and seamless AI integration. With ctx, users can create structured markdown documents, save context files, and serve context through an MCP server for real-time assistance. The tool simplifies the process of sharing project information with AI assistants, making AI conversations smarter and easier.

Memento MCP is a scalable, high-performance knowledge graph memory system designed for LLMs. It offers semantic retrieval, contextual recall, and temporal awareness to any LLM client supporting the model context protocol. The system is built on core concepts like entities and relations, utilizing Neo4j as its storage backend for unified graph and vector search capabilities. With advanced features such as semantic search, temporal awareness, confidence decay, and rich metadata support, Memento MCP provides a robust solution for managing knowledge graphs efficiently and effectively.

TunaCode CLI is an AI-powered coding assistant that provides a command-line interface for developers to enhance their coding experience. It offers features like model selection, parallel execution for faster file operations, and various commands for code management. The tool aims to improve coding efficiency and provide a seamless coding environment for developers.

The Wikipedia MCP Server is a Model Context Protocol (MCP) server that provides real-time access to Wikipedia information for Large Language Models (LLMs). It allows AI assistants to retrieve accurate and up-to-date information from Wikipedia to enhance their responses. The server offers features such as searching Wikipedia, retrieving article content, getting article summaries, extracting specific sections, discovering links within articles, finding related topics, supporting multiple languages and country codes, optional caching for improved performance, and compatibility with Google ADK agents and other AI frameworks. Users can install the server using pipx, Smithery, PyPI, virtual environment, or from source. The server can be run with various options for transport protocol, language, country/locale, caching, access token, and more. It also supports Docker and Kubernetes deployment. The server provides MCP tools for interacting with Wikipedia, such as searching articles, getting article content, summaries, sections, links, coordinates, related topics, and extracting key facts. It also supports country/locale codes and language variants for languages like Chinese, Serbian, Kurdish, and Norwegian. The server includes example prompts for querying Wikipedia and provides MCP resources for interacting with Wikipedia through MCP endpoints. The project structure includes main packages, API implementation, core functionality, utility functions, and a comprehensive test suite for reliability and functionality testing.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

Airbroke is an open-source error catcher tool designed for modern web applications. It provides a PostgreSQL-based backend with an Airbrake-compatible HTTP collector endpoint and a React-based frontend for error management. The tool focuses on simplicity, maintaining a small database footprint even under heavy data ingestion. Users can ask AI about issues, replay HTTP exceptions, and save/manage bookmarks for important occurrences. Airbroke supports multiple OAuth providers for secure user authentication and offers occurrence charts for better insights into error occurrences. The tool can be deployed in various ways, including building from source, using Docker images, deploying on Vercel, Render.com, Kubernetes with Helm, or Docker Compose. It requires Node.js, PostgreSQL, and specific system resources for deployment.

aiohttp_security is a library that provides identity and authorization for aiohttp.web. It offers features for handling authorization via cookies and supports aiohttp-session. The library includes examples for basic usage and database authentication, along with demos in the demo directory. For development, the library requires installation of specific requirements listed in the requirements-dev.txt file. aiohttp_security is licensed under the Apache 2 license.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. It supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled APIs. The tool generates JUnit tests in Java or Kotlin, focusing on fault detection, self-contained tests, SQL handling, and authentication. Known limitations include manual driver creation for whitebox testing and longer execution times for better results. EvoMaster has been funded by ERC and RCN grants.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

Gemini ChatUp is a chat application utilizing the Google GeminiPro API Key. It supports responsive layout and can store multiple sets of conversations with customizable parameters for each set. Users can log in with a test account or provide their own API Key to deploy the feature. The application also offers user authentication through Edge config in Vercel, allowing users to add usernames and passwords in JSON format. Local deployment is possible by installing dependencies, setting up environment variables, and running the application locally.

The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.

Obot is an open source AI agent platform that allows users to build agents for various use cases such as copilots, assistants, and autonomous workflows. It offers integration with leading LLM providers, built-in RAG for data, easy integration with custom web services and APIs, and OAuth 2.0 authentication.

DocsGPT is an open-source documentation assistant powered by GPT models. It simplifies the process of searching for information in project documentation by allowing developers to ask questions and receive accurate answers. With DocsGPT, users can say goodbye to manual searches and quickly find the information they need. The tool aims to revolutionize project documentation experiences and offers features like live previews, Discord community, guides, and contribution opportunities. It consists of a Flask app, Chrome extension, similarity search index creation script, and a frontend built with Vite and React. Users can quickly get started with DocsGPT by following the provided setup instructions and can contribute to its development by following the guidelines in the CONTRIBUTING.md file. The project follows a Code of Conduct to ensure a harassment-free community environment for all participants. DocsGPT is licensed under MIT and is built with LangChain.

This repository contains the source code for the Apache Airflow website, including directories for archived documentation versions, landing pages, license templates, and the Sphinx theme. To work on the site locally, users need to install coreutils, Node.js, NPM, and HUGO, and run specific scripts provided in the repository. Contributors can refer to the contributor's guide for detailed instructions on how to contribute to the website.

Lumentis is a tool that allows users to generate beautiful and comprehensive documentation from meeting transcripts and large documents with a single command. It reads transcripts, asks questions to understand themes and audience, generates an outline, and creates detailed pages with visual variety and styles. Users can switch models for different tasks, control the process, and deploy the generated docs to Vercel. The tool is designed to be open, clean, fast, and easy to use, with upcoming features including folders, PDFs, auto-transcription, website scraping, scientific papers handling, summarization, and continuous updates.

Dify Docs is a repository that houses the documentation website code and Markdown source files for docs.dify.ai. It contains assets, content, and data folders that are licensed under a CC-BY license.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

The Microsoft Semantic Kernel Documentation GitHub repository contains technical product documentation for Semantic Kernel. It serves as the home of technical content for Microsoft products and services. Contributors can learn how to make contributions by following the Docs contributor guide. The project follows the Microsoft Open Source Code of Conduct.

anythingllm-docs is a documentation repository for the AnythingLLM project. It contains detailed guides, setup instructions, and information on features and legal aspects of the project. The repository structure is organized into public, pages, components, and configuration files. Users can contribute by creating issues and pull requests following specific guidelines. The project is licensed under the MIT License and has been migrated to NextJS with the help of @ShadowArcanist.

RepoAgent is an LLM-powered framework designed for repository-level code documentation generation. It automates the process of detecting changes in Git repositories, analyzing code structure through AST, identifying inter-object relationships, replacing Markdown content, and executing multi-threaded operations. The tool aims to assist developers in understanding and maintaining codebases by providing comprehensive documentation, ultimately improving efficiency and saving time.