Relay

Product Introduction

1. Definition: Relay is a cross-AI context management platform and browser extension. Technically, it is a tool that leverages the Model Context Protocol (MCP) to create, maintain, and synchronize a structured, living project brief across disparate AI chat interfaces and integrated development environment (IDE) agents.
2. Core Value Proposition: Relay exists to eliminate the repetitive, manual task of copying and pasting project context (decisions, tasks, constraints, and progress) into every new AI chat session. Its primary value is providing persistent, synchronized project memory that travels with the user across tools like ChatGPT, Claude, Gemini, and IDE agents like Cursor and Claude Code, ensuring continuity and efficiency in AI-assisted workflows.

Main Features

1. Auto-Capture & Context Extraction: Relay operates silently in the background during AI chat sessions. It uses natural language processing (NLP) models to automatically identify and extract key project elements—such as technical decisions, outlined tasks, and stated constraints—from the conversation transcript. This happens without any manual saving or prompting from the user.
2. Living Project Briefs: The extracted data is structured into a dynamic, centralized project brief. This brief is not a static document but a "living" one that updates automatically as new information is captured from chats. It serves as a single source of truth for project context, accessible from any connected surface.
3. MCP (Model Context Protocol) Integration: This is the core technical integration. Relay implements MCP, an open standard for AI tool communication, as a server. This allows any MCP-compatible IDE agent (e.g., Cursor, Claude Code, Windsurf, GitHub Copilot) to directly read from and write to the Relay project brief. This enables true bidirectional sync between browser-based AI chats and code-focused AI agents.
4. One-Click Context Injection: When starting a fresh chat in a supported AI platform (e.g., a new ChatGPT window), users can inject their entire, up-to-date project brief into the new conversation with a single click. This pre-populates the chat with all relevant prior context, allowing the user to continue work seamlessly.
5. Cross-Surface Synchronization: Decisions made in a browser chat with Claude are automatically captured and reflected in the project brief. An IDE agent like Cursor, via MCP, can then read that updated brief. Conversely, progress or code decisions made by the IDE agent can be written back to the brief and become available for the next browser session, creating a closed-loop system.

Problems Solved

1. Pain Point: Context Fragmentation and Repetition: Developers and technical professionals waste significant time and mental energy re-explaining their project's stack, recent decisions, and current status every time they open a new AI chat tab or switch between an AI coding assistant and a conversational AI.
2. Pain Point: Lack of Project Memory in AI Workflows: AI chat sessions are inherently stateless and isolated. Without a tool like Relay, there is no native mechanism for an AI to remember project-specific details from past conversations, leading to inconsistent advice and broken continuity.
3. Target Audience: The primary users are software engineers, developers, and technical builders who regularly use multiple AI tools (e.g., ChatGPT for brainstorming, Claude for analysis, Cursor for coding). Secondary users include product managers, startup founders, and technical leads who use AI for planning and documentation and need consistency across discussions.
4. Use Cases:
   • A developer discussing authentication architecture with ChatGPT, then needing the same context when asking Claude Code to implement the related RLS policies in Supabase.
   • A founder refining their product roadmap across multiple Gemini sessions over several days, needing each new chat to be aware of all prior decisions.
   • A team using shared project briefs to keep AI-assisted work aligned, ensuring all members and their respective AI tools are operating from the same set of constraints and goals.

Unique Advantages

1. Differentiation: Unlike simple note-taking apps or manual copy-pasting, Relay provides automated, intelligent capture and true interoperability between chat-based AIs and IDE-based agents. Competitors may offer session history or basic prompts, but Relay uniquely bridges the gap between conversational AI and development environments via the open MCP standard.
2. Key Innovation: The strategic implementation of the Model Context Protocol (MCP) as the synchronization layer is its key technical innovation. This allows Relay to function not just as a passive recorder, but as an active, standardized memory server for the entire AI tool ecosystem, enabling a level of toolchain integration previously unavailable.

Frequently Asked Questions (FAQ)

1. How does Relay capture context without me manually saving it? Relay uses specialized AI models to analyze your chat conversations in real-time. It automatically identifies and extracts structured information like technical decisions, action items (tasks), and project limitations (constraints), then updates your project brief silently in the background.
2. What is MCP and why is it important for Relay? MCP (Model Context Protocol) is an open-source standard that allows different AI applications to communicate and share structured context. Relay uses MCP as a bridge, enabling your IDE's AI agent (like Cursor) to directly read your project's latest decisions and write back its own progress, creating seamless sync between your browser chats and coding environment.
3. Is my chat data private and secure with Relay? According to Relay's policy, your data is private. The context capture and processing are designed to respect your privacy, focusing only on extracting structured project data to build your brief. It is advised to review their official Privacy Policy for specific data handling and storage details.
4. Can Relay work with any AI model or IDE? Relay works with major browser-based AI platforms including OpenAI's ChatGPT, Anthropic's Claude, Google's Gemini, xAI's Grok, Perplexity, and DeepSeek. For IDEs, it supports any agent compatible with the Model Context Protocol (MCP), such as Cursor, Claude Code, Windsurf, Codex, and GitHub Copilot.
5. What's the difference between the Free and paid Starter/Pro plans? The Free plan is for trying core features with limits (e.g., 2 active projects, 5 MCP reads/day). The Starter plan ($6/month) increases limits for solo builders (5 projects, 120 MCP reads/day). The Pro plan ($12/month) is for power users, offering higher limits, advanced features like aggressive autonomy with conflict resolution, and priority support for deep workflow integration.