convex-agents

Create persistent, stateful AI agents with thread management and tool integration.

1|1|Updated Apr 13, 2026

Search Tags:#rag #tooling #streaming #ai-agent #workflows #convex #stateful

Ready to run

npx skills add https://github.com/Cheggin/request-for-startups --skill convex-agents-cheggin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: convex-agents
Source: https://github.com/Cheggin/request-for-startups/tree/main/skills/convex-agents
Command: npx skills add https://github.com/Cheggin/request-for-startups --skill convex-agents-cheggin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Building AI agents that can maintain context, coordinate multiple tasks, and operate over long-running sessions often requires bespoke scaffolding and state management. Convex Agents provides a ready-made framework to create persistent, stateful agents that can remember context, manage threads, and orchestrate complex workflows.

Core Features & Use Cases

Persistent state and conversation history that survives restarts.
Real-time streaming responses for interactive experiences.
Tool integration to execute actions, fetch data, and perform tasks.
Durable workflows to coordinate multi-step processes.
Retrieval augmented generation (RAG) for knowledge access.

Quick Start

Instantiate a Convex agent and start a persistent chat workflow.

Frequently Asked Questions about convex-agents

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build stateful AI agents that maintain context across long-running sessions?▼

Build stateful AI agents by using a framework that provides persistent state and conversation history, ensuring context survives session restarts. This approach manages extended conversations and durable workflows without bespoke state scaffolding.

What is the best way to manage threaded conversations and multi-agent workflows in a persistent environment?▼

Threaded conversations and multi-agent workflows are managed through a stateful framework that coordinates multi-step processes. It provides durable workflows and thread management to orchestrate complex tasks across extended interactions.

How do I integrate external tools and retrieval-augmented generation into an AI agent?▼

Integrate external tools and retrieval-augmented generation by using an agent framework with built-in tool integration and RAG support. This allows agents to fetch data, execute actions, and access knowledge during reasoning.

Can I stream real-time AI agent responses while managing durable workflows?▼

Yes, you can stream real-time AI agent responses while managing durable workflows. The framework supports real-time streaming for interactive experiences alongside persistent state for coordinating long-running tasks.

Do I need a specific backend platform to run persistent agents with durable workflows?▼

You need a backend platform that supports durable execution and stateful workflows to run persistent agents. The framework relies on a stateful backend component to manage conversation history and coordinate multi-step processes reliably.

Why does my AI agent lose conversation history when the session restarts?▼

AI agents lose conversation history when the session restarts if they lack persistent state management. A stateful agent framework with durable workflows ensures conversation context and history survive restarts automatically.