
Groovy is an AI agent command center that unifies multiple AI coding agents—such as Claude Code and Codex—into a single, local dashboard. It is designed for developers, engineering teams, and technical leads who need to coordinate work across several agents without switching contexts. The core value lies in providing real-time visibility, agent-to-agent handoffs, and consolidated planning, all while keeping data on the user's machine. This makes it a privacy-first alternative to cloud-based agent platforms. The product also extends to non-coding tasks like meeting coordination, social monitoring, and analytics, making it a comprehensive personal assistant for knowledge workers.
The primary problem Groovy solves is the fragmentation of AI agent outputs. When using multiple agents for coding, planning, or analysis, users often lose track of what each agent is doing, duplicate work, or miss dependencies. Groovy addresses this with a multi-agent view that shows each agent's current task, plan, and blocker side by side. Agents can also pass context to each other via handshake, ensuring that follow-up tasks start from where the previous agent left off. This is crucial for complex workflows where agents need to collaborate sequentially or in parallel. Without such coordination, users waste time re-explaining requirements and restarting agent sessions.
First major feature group: Multi-agent view and agent handshake. The multi-agent view allows users to watch all active coding agents simultaneously in a single interface. Instead of guessing which chat holds the current plan or blocker, users see each agent's status at a glance. The agent handshake feature takes this further by enabling agents to pass context, decisions, and next actions directly to each other. For example, a planner agent can hand off a detailed implementation plan to a coding agent, which then passes completed code to a reviewer agent. This prevents work from restarting from scratch and ensures continuity across agent roles. Both features reduce communication overhead and speed up complex multi-step tasks.
Second major feature group: Consolidated plans and skills/.md instructions. Groovy automatically turns scattered agent notes into one readable plan that users can approve, edit, or hand to the next agent. This consolidation eliminates the need to manually copy-paste outputs from different chat sessions. Additionally, users can assign skills, repo instruction files, or Markdown playbooks to any agent. This gives each agent the precise context it needs—such as coding standards, project guidelines, or step-by-step workflows—without requiring the user to re-enter instructions. The combination of consolidated plans and contextual instructions ensures that agents work consistently and efficiently, adhering to team practices.
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Third feature group: CLI integrations and extension packs. Groovy allows companies to turn their product's CLI or API into a set of typed tools that agents can invoke. Using extension packs, developers describe actions with names, descriptions, input schemas, and output schemas. For CLIs, Groovy supports safe argv templates that execute only approved command shapes. These integrations run through a customer runner inside the user's environment, preserving network security. Each tool has a risk level and auth scope, and Groovy handles approval states, encrypted secrets, audit events, and runtime traces. This makes Groovy a secure gateway for automating external tools without giving agents raw shell access.
How the product works overall: Groovy operates via a local connector that runs on the user's machine, providing access to browser, files, terminal, and local tools with permission. Users create a Groovy account, download the connector, and connect their own AI provider API keys (e.g., OpenAI, Anthropic, Groq). The account portal manages licenses, devices, source snapshots, and updates. Once installed, users can invoke Groovy from WhatsApp, Telegram, or the web dashboard. The system orchestrates requests, routes them to appropriate agents, and returns results. For enterprise teams, Groovy supports multiple members organized into Cells—dedicated spaces for agents, people, and KPIs. This architecture ensures data stays local while enabling collaboration and accountability.
Concrete use cases: A development team uses Groovy to coordinate a planner, coder, and reviewer agent during a sprint. The planner breaks down a feature, hands off to the coder, who uses repository skills to write code, then passes to the reviewer for quality checks—all visible in the multi-agent view. A marketing analyst queries ad performance across Google Ads, TikTok, and Facebook using natural language from WhatsApp, getting structured reports without logging into each platform. A product manager sets up a Cell with sales, operations, and product agents, each tracked with KPIs like pipeline growth and launch progress. A personal user coordinates meetings by asking Groovy to check team calendars and propose optimal times, then creates events.
Target users include individual developers who use multiple coding agents, engineering teams that need agent orchestration, marketing and operations teams that benefit from natural language analytics, and enterprises requiring governance and source access. Groovy runs on macOS 12+ (Apple Silicon) and Windows 10+ (x64). Pricing is $49.99/year for personal use with two devices, and enterprise licensing through sales for commercial use with modification rights. The product emphasizes privacy by keeping data local and letting users bring their own API keys. Groovy's command center approach reduces context-switching and makes agent collaboration transparent, making it a vital tool for anyone serious about leveraging multiple AI agents efficiently.
Groovy is designed for software developers and engineering teams who work with multiple AI coding agents such as Claude Code and Codex. It also serves marketing analysts, operations managers, and product teams who need natural language analytics and agent coordination. Enterprise teams requiring source access, internal tool integrations, and KPI tracking will find the Cells feature valuable. Personal users seeking a private local AI assistant for meetings, knowledge retrieval, and coding tasks are also a core audience. The product is suitable for anyone who wants to orchestrate multiple AI agents without sacrificing data privacy or control over API keys.