Fetcher MCP is a server tool designed for fetching web page content using Playwright headless browser. It supports JavaScript execution, intelligent content extraction, flexible output formats, parallel processing, resource optimization, robust error handling, and configurable parameters. The tool provides features like fetching web page content from a specified URL, batch retrieving content from multiple URLs, and offers fine-grained control over various parameters. Fetcher MCP is ideal for users looking to scrape dynamic web content efficiently and reliably.

An open-source mono-repository containing the MyCoder agent and CLI. It leverages Anthropic's Claude API for intelligent decision making, has a modular architecture with various tool categories, supports parallel execution with sub-agents, can modify code by writing itself, features a smart logging system for clear output, and is human-compatible using README.md, project files, and shell commands to build its own context.

Hayhooks is a tool that simplifies the deployment and serving of Haystack pipelines as REST APIs. It allows users to wrap their pipelines with custom logic and expose them via HTTP endpoints, including OpenAI-compatible chat completion endpoints. With Hayhooks, users can easily convert their Haystack pipelines into API services with minimal boilerplate code.

MCPHost is a CLI host application that enables Large Language Models (LLMs) to interact with external tools through the Model Context Protocol (MCP). It acts as a host in the MCP client-server architecture, allowing language models to access external tools and data sources, maintain consistent context across interactions, and execute commands safely. The tool supports interactive conversations with Claude 3.5 Sonnet and Ollama models, multiple concurrent MCP servers, dynamic tool discovery and integration, configurable server locations and arguments, and a consistent command interface across model types.

cursor-tools is a CLI tool designed to enhance AI agents with advanced skills, such as web search, repository context, documentation generation, GitHub integration, Xcode tools, and browser automation. It provides features like Perplexity for web search, Gemini 2.0 for codebase context, and Stagehand for browser operations. The tool requires API keys for Perplexity AI and Google Gemini, and supports global installation for system-wide access. It offers various commands for different tasks and integrates with Cursor Composer for AI agent usage.

llm-vscode is an extension designed for all things LLM, utilizing llm-ls as its backend. It offers features such as code completion with 'ghost-text' suggestions, the ability to choose models for code generation via HTTP requests, ensuring prompt size fits within the context window, and code attribution checks. Users can configure the backend, suggestion behavior, keybindings, llm-ls settings, and tokenization options. Additionally, the extension supports testing models like Code Llama 13B, Phind/Phind-CodeLlama-34B-v2, and WizardLM/WizardCoder-Python-34B-V1.0. Development involves cloning llm-ls, building it, and setting up the llm-vscode extension for use.

Lumos is a Chrome extension powered by a local LLM co-pilot for browsing the web. It allows users to summarize long threads, news articles, and technical documentation. Users can ask questions about reviews and product pages. The tool requires a local Ollama server for LLM inference and embedding database. Lumos supports multimodal models and file attachments for processing text and image content. It also provides options to customize models, hosts, and content parsers. The extension can be easily accessed through keyboard shortcuts and offers tools for automatic invocation based on prompts.

ppt2desc is a command-line tool that converts PowerPoint presentations into detailed textual descriptions using vision language models. It interprets and describes visual elements, capturing the full semantic meaning of each slide in a machine-readable format. The tool supports various model providers and offers features like converting PPT/PPTX files to semantic descriptions, processing individual files or directories, visual elements interpretation, rate limiting for API calls, customizable prompts, and JSON output format for easy integration.

The Google Gen AI JavaScript SDK is an experimental SDK for TypeScript and JavaScript developers to build applications powered by Gemini. It supports both the Gemini Developer API and Vertex AI. The SDK is designed to work with Gemini 2.0 features. Users can access API features through the GoogleGenAI classes, which provide submodules for querying models, managing caches, creating chats, uploading files, and starting live sessions. The SDK also allows for function calling to interact with external systems. Users can find more samples in the GitHub samples directory.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

Nuxt LLMs automatically generates llms.txt markdown documentation for Nuxt applications. It provides runtime hooks to collect data from various sources and generate structured documentation. The tool allows customization of sections directly from nuxt.config.ts and integrates with Nuxt modules via the runtime hooks system. It generates two documentation formats: llms.txt for concise structured documentation and llms_full.txt for detailed documentation. Users can extend documentation using hooks to add sections, links, and metadata. The tool is suitable for developers looking to automate documentation generation for their Nuxt applications.

LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.

june-va is a local voice chatbot that combines Ollama for language model capabilities, Hugging Face Transformers for speech recognition, and the Coqui TTS Toolkit for text-to-speech synthesis. It provides a flexible, privacy-focused solution for voice-assisted interactions on your local machine, ensuring that no data is sent to external servers. The tool supports various interaction modes including text input/output, voice input/text output, text input/audio output, and voice input/audio output. Users can customize the tool's behavior with a JSON configuration file and utilize voice conversion features for voice cloning. The application can be further customized using a configuration file with attributes for language model, speech-to-text model, and text-to-speech model configurations.

SDFX is the ultimate no-code platform for building and sharing AI apps with beautiful UI. It enables the creation of user-friendly interfaces for complex workflows by combining Comfy workflow with a UI. The tool is designed to merge the benefits of form-based UI and graph-node based UI, allowing users to create intricate graphs with a high-level UI overlay. SDFX is fully compatible with ComfyUI, abstracting the need for installing ComfyUI. It offers features like animated graph navigation, node bookmarks, UI debugger, custom nodes manager, app and template export, image and mask editor, and more. The tool compiles as a native app or web app, making it easy to maintain and add new features.

LLM Functions is a project that enables the enhancement of large language models (LLMs) with custom tools and agents developed in bash, javascript, and python. Users can create tools for their LLM to execute system commands, access web APIs, or perform other complex tasks triggered by natural language prompts. The project provides a framework for building tools and agents, with tools being functions written in the user's preferred language and automatically generating JSON declarations based on comments. Agents combine prompts, function callings, and knowledge (RAG) to create conversational AI agents. The project is designed to be user-friendly and allows users to easily extend the capabilities of their language models.

AI-video-boilerplate-simple is a free Live AI Video boilerplate for testing out live video AI experiments. It includes a simple Flask server that serves files, supports live video from various sources, and integrates with Roboflow for AI vision. Users can use this template for projects, research, business ideas, and homework. It is lightweight and can be deployed on popular cloud platforms like Replit, Vercel, Digital Ocean, or Heroku.

Fetcher MCP is a server tool designed for fetching web page content using Playwright headless browser. It supports JavaScript execution, intelligent content extraction, flexible output formats, parallel processing, resource optimization, robust error handling, and configurable parameters. The tool provides features like fetching web page content from a specified URL, batch retrieving content from multiple URLs, and offers fine-grained control over various parameters. Fetcher MCP is ideal for users looking to scrape dynamic web content efficiently and reliably.

Podwise is an AI knowledge management app designed specifically for podcast listeners. With the Podwise platform, you only need to follow your favorite podcasts, such as "Hardcore Hackers". When a program is released, Podwise will use AI to transcribe, extract, summarize, and analyze the podcast content, helping you to break down the hard-core podcast knowledge. At the same time, it is connected to platforms such as Notion, Obsidian, Logseq, and Readwise, embedded in your knowledge management workflow, and integrated with content from other channels including news, newsletters, and blogs, helping you to improve your second brain 🧠.

Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

ScrapeGraphAI is a Python library that uses Large Language Models (LLMs) and direct graph logic to create web scraping pipelines for websites, documents, and XML files. It allows users to extract specific information from web pages by providing a prompt describing the desired data. ScrapeGraphAI supports various LLMs, including Ollama, OpenAI, Gemini, and Docker, enabling users to choose the most suitable model for their needs. The library provides a user-friendly interface through its `SmartScraper` class, which simplifies the process of building and executing scraping pipelines. ScrapeGraphAI is open-source and available on GitHub, with extensive documentation and examples to guide users. It is particularly useful for researchers and data scientists who need to extract structured data from web pages for analysis and exploration.

Chaindesk is a no-code platform that allows users to easily set up a semantic search system for personal data without technical knowledge. It supports loading data from various sources such as raw text, web pages, files (Word, Excel, PowerPoint, PDF, Markdown, Plain Text), and upcoming support for web sites, Notion, and Airtable. The platform offers a user-friendly interface for managing datastores, querying data via a secure API endpoint, and auto-generating ChatGPT Plugins for each datastore. Chaindesk utilizes a Vector Database (Qdrant), Openai's text-embedding-ada-002 for embeddings, and has a chunk size of 1024 tokens. The technology stack includes Next.js, Joy UI, LangchainJS, PostgreSQL, Prisma, and Qdrant, inspired by the ChatGPT Retrieval Plugin.

Auto-News is an automatic news aggregator tool that utilizes Large Language Models (LLM) to pull information from various sources such as Tweets, RSS feeds, YouTube videos, web articles, Reddit, and journal notes. The tool aims to help users efficiently read and filter content based on personal interests, providing a unified reading experience and organizing information effectively. It features feed aggregation with summarization, transcript generation for videos and articles, noise reduction, task organization, and deep dive topic exploration. The tool supports multiple LLM backends, offers weekly top-k aggregations, and can be deployed on Linux/MacOS using docker-compose or Kubernetes.

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

1filellm is a command-line data aggregation tool designed for LLM ingestion. It aggregates and preprocesses data from various sources into a single text file, facilitating the creation of information-dense prompts for large language models. The tool supports automatic source type detection, handling of multiple file formats, web crawling functionality, integration with Sci-Hub for research paper downloads, text preprocessing, and token count reporting. Users can input local files, directories, GitHub repositories, pull requests, issues, ArXiv papers, YouTube transcripts, web pages, Sci-Hub papers via DOI or PMID. The tool provides uncompressed and compressed text outputs, with the uncompressed text automatically copied to the clipboard for easy pasting into LLMs.

Agently Daily News Collector is an open-source project showcasing a workflow powered by the Agent ly AI application development framework. It allows users to generate news collections on various topics by inputting the field topic. The AI agents automatically perform the necessary tasks to generate a high-quality news collection saved in a markdown file. Users can edit settings in the YAML file, install Python and required packages, input their topic idea, and wait for the news collection to be generated. The process involves tasks like outlining, searching, summarizing, and preparing column data. The project dependencies include Agently AI Development Framework, duckduckgo-search, BeautifulSoup4, and PyYAM.