Enables AI agents to browse and interact with JavaScript-rendered websites stealthily, and to delegate research or automation tasks to sub-agents that can cite sources and produce reusable scripts, with full logging and a live dashboard.
Ultra-lightweight headless browser for AI agents. Provides MCP tools for navigating URLs, extracting structured content, and building autonomous agent workflows.
Enables MCP clients like Codex to delegate coding tasks to DeepSeek Harness, reusing the same Web-visible session for feedback and keeping the conversation in the Harness Web UI.
Enables AI shopping agents to search products, check stock, apply promotions, manage cart sessions, and create cryptographically signed checkout sessions on e-commerce storefronts, while giving merchants analytics into agent intent and catalog demand gaps.
A Node.js application that connects WhatsApp Web with AI models through the Model Context Protocol, enabling automated messaging, contact management, and group chat functionality through AI-driven workflows.
Exposes browser-testing capabilities—including navigation, clicking, typing, form submission, verification, and screenshots—so clients can discover the supported Playwright actions. It also builds structured testing requirements from a supplied website and task description, ready for plan generation and execution.
Enables AI agents to persist, retrieve, and share source-linked memory across sessions via MCP tools, backed by PostgreSQL with project/session management, decision tracking, keyword search, and cross-host context handoff.
Enables MCP clients to create and manage parallel ChatGPT webpage conversations as subagents, dispatch and await tasks across multiple sessions, preserve context for follow-ups, and relay completed results through native notifications.
Enables structured multi-LLM critique of concepts using three specialized agents (Innovation, Ethics, Security) with multi-vendor LLM support. Provides 13 free tools for validation, template management, and coordination.
Enables supervised, visible control of a Windows desktop from an MCP client, providing real mouse and keyboard input, screenshots, local safety controls, and a teaching mode for guidance without injection.
Allows AI agents to control and interact with VS Code webviews by providing tools for navigation, element interaction, and state retrieval. It facilitates automated tasks like clicking elements, inputting text, and reading the DOM structure within a VS Code tab.
Enables agent-driven CAD design through deterministic source files (.kcad.ts), including model evaluation, validation, and export to STEP/STL via MCP tools for review and introspection.