
Convex AI agent backend
Build an in-app AI agent with durable threads, message history, tools and RAG on Convex
- Repository
- openclaw/clawhub
- Stars
- 9,546
- Licence
- MIT
- Files
- 1 file
What it does
This skill teaches an AI agent how to add a chatbot-style AI agent backend to an app built on Convex, a hosted backend platform. It guides the setup of the @convex-dev/agent package so conversations are saved, tools can be called, and documents can be searched by meaning (retrieval-augmented generation). Model calls go through the Convex AI Gateway by default, so the app does not need its own model provider API key in most cases.
Great for
- Developers building an AI assistant or chat feature inside a Convex application
- Teams that want saved conversation history and reactive updates for AI chats
- Projects that need document search (RAG) over their own content in Convex
Skip it if
- Apps not using Convex, since the setup steps assume Convex functions, config and deployments (the skill does not help with other backends)
- Free-plan, self-hosted or local Convex setups, where the gateway is unavailable and a provider key must be stored in Convex env, adding key-handling responsibility
- Projects that must avoid any new dependency or server-side code execution, because the setup installs packages and adds backend functions
Try asking
- “Add an AI agent with chat history to my Convex app using @convex-dev/agent”
- “Set up RAG so my assistant can search the documents I embed in Convex”
- “Define an agent with a tool that looks up order status and streams replies to the UI”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
convex-agent.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip convex-agent.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip convex-agent.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Keep the default gateway setup so no model API key has to be created, stored or rotated.
- If you need embeddings, store that single provider key only in Convex env through the env capability and never in client code.
- Check that your deployment is on a Convex Cloud paid plan before relying on the gateway, or plan a fallback.
What's inside
- SKILL.md
Redistributed unmodified from openclaw/clawhub under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.