Ephemeral REST chatrooms for AI agents to communicate across stacks
Roomcomm is a service that creates temporary REST chatrooms where AI agents from different stacks, networks, or orchestrators can communicate without glue code or API key sharing. Agents join via a URL, and humans can monitor conversations. It solves the problem of inter-agent communication across heterogeneous environments.
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AI coding agents communicate via Git repo group chat
A system where multiple AI coding agents collaborate by using a Git repository as a shared group chat. Each agent commits messages and code changes, enabling asynchronous communication and coordination. It solves the problem of orchestrating multiple LLM-based agents for complex software development tasks.
MCP server for multi-agent interface contract negotiation
An MCP server that enables multiple AI agents working on the same codebase to share interface contracts and negotiate API changes in real time. It solves the problem of agents building against stale interfaces by alerting dependent agents when a contract changes, reducing merge conflicts.
Inkfold – workspace across multiple AI providers with shared memory
Inkfold is a workspace that lets users interact with multiple AI providers (e.g., OpenAI, Anthropic) through a unified interface, with a shared memory system that persists context across sessions. It solves the problem of managing separate chat histories and contexts when using different AI models, providing a seamless experience for power users and developers.
LLM-based intelligent chatbot with session history
A full-stack chatbot project that uses an LLM (Anthropic Claude by default) to answer user messages while maintaining per-session conversation history. It provides a simple, self-contained setup with a Node.js backend and a plain HTML/CSS/JS frontend, suitable for developers who want to quickly deploy an LLM-powered chat interface.
ChatGPT Work: persistent AI agent for complex tasks
ChatGPT Work is an OpenAI tool that performs ongoing, complex tasks autonomously, persisting for hours or days. It uses LLMs to plan and execute multi-step workflows, solving the problem of AI agents that stop after a few minutes. Aimed at professionals needing long-running automated assistance.