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A Model Context Provider (MCP) server with accompanying Chrome extension that allows AI applications to control and automate your real browser using the MCP protocol.
Pulls up-to-date, version-specific docs and code examples straight from a library's source into your AI coding agent's prompt, killing hallucinated APIs from stale training data. Works as an MCP server or via a ctx7 CLI plus skill.
Provides a collaborative API development platform for designing, testing, documenting, and monitoring APIs — with sharable Collections, mock servers, CLI, and AI-driven features (Agent Mode, AI Agent Builder, MCP Server) to automate API workflows.
Generates instant REST and GraphQL APIs and a visual management Studio on top of any SQL database so teams can manage content and build apps without schema rework. Includes a built-in AI Assistant and a native MCP server that let permissioned AI agents read and write live data under the same role-based policies.
Manages polyglot monorepos by caching unchanged outputs and running only affected tasks. Built with Rust and extensible in TypeScript; includes integrated CI features (remote caching, task distribution) and AI-native tooling such as a CLI optimized for autonomous agents and self-healing CI.
Manages OAuth, credential storage, API proxying, and deployable TypeScript integration functions so products and AI agents can access 800+ external APIs. Includes AI-assisted function generation, a production runtime with scaling and observability, and cloud or self-hosted deployment options.
Exposes a self-hosted WhatsApp HTTP/REST API that runs a real WhatsApp Web instance so apps and AI agents can read/send messages, manage contacts, and automate flows. Offers three engine modes (WEBJS, NOWEB, GOWS), Docker images, and MCP support; relies on WhatsApp Web so blocking risk exists.
Collects metrics, distributed traces, and continuous profiles via eBPF with zero code instrumentation, covering apps in any language plus gateways, service meshes, databases, and queues. Profiling adds under 1% overhead.
Provides a searchable, community-curated library of prompts for chat and LLM models, with a browsable site, CSV/Hugging Face dataset, an interactive prompting guide, and self-hosting options. Focused on prompt examples and community contributions for ChatGPT and other LLMs.
Connect LLMs to major chat platforms so teams can build, deploy, and operate multi-platform AI chatbots and agents. Provides multi-platform adapters, a plugin marketplace, an MCP server and built-in RAG plus production features like access control, rate limiting and monitoring.
