agor

Product Introduction

1. Agor is a next-generation agent orchestration platform designed for AI-driven coding workflows, combining a spatial canvas with multiplayer collaboration capabilities.
2. The core value lies in unifying disparate AI coding tools like Claude Code, Codex, and Gemini into a single collaborative workspace, enabling seamless coordination between human developers and AI agents.

Main Features

1. The spatial canvas provides a visual interface with worktrees and zones for organizing codebases, AI-generated outputs, and task-specific contexts in a hierarchical structure.
2. MCP (Multi-Agent Control Protocol) servers enable scalable orchestration of AI agents, while worktree management ensures version-controlled branching and merging of AI-generated code.
3. Live collaboration features include real-time cursor tracking, threaded comments, and shared editing sessions synchronized across distributed teams and AI agents.

Problems Solved

1. Eliminates fragmentation between standalone AI coding tools by providing a unified spatial layer for cross-platform agent coordination and human-AI interaction.
2. Targets software engineering teams, AI researchers, and developers working with multiple code-generation models who require structured collaboration frameworks.
3. Enables use cases like collaborative code reviews with AI assistants, multi-agent prompt engineering workflows, and real-time debugging sessions with contextual AI support.

Unique Advantages

1. Unlike isolated AI coding environments, Agor implements spatial organization of code artifacts with persistent contextual memory accessible to all integrated agents.
2. The platform introduces worktree-based versioning specifically optimized for AI-generated code iterations, including automated diff analysis for model outputs.
3. Competitive differentiation stems from the combination of multiplayer workspace mechanics with enterprise-grade agent orchestration APIs, supporting custom AI tool integrations.

Frequently Asked Questions (FAQ)

1. How does Agor handle conflicts between AI-generated code versions? Agor utilizes MCP servers to track code provenance and implements three-way merging algorithms optimized for machine-generated content across worktree branches.
2. Can teams deploy private AI agents into the workspace? The platform supports Docker-based agent deployments with secure sandboxing, allowing custom models to operate within the spatial canvas alongside pre-integrated AI tools.
3. What collaboration features exist for non-coders? Stakeholders can annotate worktrees with visual comments, attach requirements documents to zones, and monitor AI progress through real-time activity feeds without direct code interaction.
4. How does the spatial canvas improve AI performance? By maintaining persistent context through zone-specific memory caches and worktree linkages, AI agents reduce redundant computations and maintain task continuity across coding sessions.
5. What security measures protect proprietary code? All workspace data is encrypted in transit and at rest, with role-based access controls, audit logging, and optional on-premises MCP server deployments for regulated environments.