openwork

Product Introduction

1. Definition: OpenWork is an open-source, cross-platform desktop application (macOS, Windows, Linux) that functions as a collaborative AI agent orchestration platform. Technically, it is a local-first client built on the OpenCode framework, integrating with the Model Context Protocol (MCP) to manage and execute AI-powered workflows.
2. Core Value Proposition: It exists to solve the problem of fragmented and non-reproducible AI workflows by enabling individuals and teams to centrally manage over 50 Large Language Models (LLMs) with their own API keys, then seamlessly package, share, and execute complex automation setups across an organization. Its primary value is in moving beyond single-agent prompting to collaborative, multi-step automation.

Main Features

1. Multi-LLM Orchestration with BYOK (Bring Your Own Keys): OpenWork provides a unified interface to configure and use models from 50+ providers, including OpenAI, Anthropic, Google, and local models. Users connect their own API keys, ensuring cost control and vendor flexibility. The platform acts as a router, sending prompts directly from the local desktop app to the chosen provider's API.
2. One-Click Skill & MCP Sharing: This is a core technical innovation. Users can develop skills (defined in SKILL.md files), MCP servers, plugins, and configurations locally. OpenWork allows them to bundle these components into a single, shareable link. Teammates can import this entire setup with one click, instantly gaining access to the same tools and automations without manual terminal configuration or technical setup.
3. Native MCP Client Integration: OpenWork functions as a powerful MCP server (https://api.openworklabs.com/mcp/agent). It provides verified OAuth-based integration guides for major AI agent clients like Claude Code, Cursor, Codex, ChatGPT Desktop, VS Code, and OpenCode. This allows developers to point their preferred coding agent directly at their OpenWork organization's shared skills and resources, bridging individual and team workflows.
4. Visual Workflow Execution & Audit Trail: The interface provides a clear execution timeline for automated tasks. For example, a "Like Twitter replies and export users" skill shows a step-by-step breakdown (e.g., "1 step - Navigates to tweet URL," "4 steps - Scrolls and clicks 'like'") and confirms results. This offers transparency, debugging insight, and a reproducible audit log for automated actions.

Problems Solved

1. Pain Point: Fragmented AI Tooling and Knowledge Silos. Teams using different AI agents (Claude Code, Cursor, etc.) struggle to share effective prompts, custom tools (MCPs), and workflows. This leads to duplication of effort and inconsistent results.
2. Target Audience: Development teams, engineering managers, DevOps professionals, technical operations teams, and enterprises implementing AI-assisted workflows. It specifically targets users of MCP-compatible agents who need to standardize and scale automation.
3. Use Cases: Standardizing code review processes across a team; sharing a packaged "competitor analysis" skill that automates web scraping and report generation; onboarding new engineers with a single link that installs all team-specific AI helpers; executing complex, multi-step browser automations (like social media engagement analysis) defined as reproducible skills.

Unique Advantages

1. Differentiation vs. Claude Cowork: Unlike the closed, vendor-locked Claude Cowork, OpenWork is open-source, supports multi-vendor LLMs (not just Anthropic), and emphasizes local-first execution where files remain on the user's machine. Its team-sharing model via links is more granular and developer-centric.
2. Key Innovation: The "Shareable Setup Link" technology. The ability to cryptographically package a local workspace configuration—including skills, MCP server connections, and environment variables—into a single URL that replicates that environment for another user is a significant workflow innovation. It turns complex configuration into a portable, one-click import operation.

Frequently Asked Questions (FAQ)

1. Is OpenWork really free and how does it make money? Yes, the core desktop application is completely free and open-source; you pay only for the LLM API keys you use. The company offers paid Team Starter plans (starting at $10/seat/month after 5 free seats) for cloud API access and an Extension Marketplace, and Enterprise plans with features like SSO and custom inference hosting.
2. Does OpenWork store or process my data on its servers? In the default desktop mode, no. Your files and data remain on your local machine, and prompts are sent directly from your app to your configured LLM provider's API. Optional hosted cloud workers run on sandboxed infrastructure for specific tasks.
3. What is the difference between OpenWork and OpenCode? OpenCode is the underlying open-source framework and code editor for building AI-native applications. OpenWork is a specific desktop application built on OpenCode, designed as a ready-to-use, end-user product for AI workflow orchestration and team collaboration.
4. Can I use OpenWork without being a developer? Yes. While it has deep capabilities for developers, the desktop app is point-and-click. The primary use case for non-developers is importing and running skills shared by teammates via a link, which requires no coding or terminal knowledge.
5. Which AI agent clients work best with OpenWork? OpenWork provides a verified native integration with OpenCode. It provides detailed setup guides for Codex, Cursor, ChatGPT Desktop, Claude Code, and VS Code. Any MCP client that supports remote Streamable HTTP servers with OAuth can connect using the provided server URL.