A command for adding an AI agent backend to a Convex app. It supports durable conversation threads, saved message history, tool calls, and retrieval-augmented generation (RAG), which lets an agent search stored documents when answering.

Use it to install the Convex agent component, define tools and instructions, stream model responses, save thread history, and build a RAG document search system.

It provides the backend pieces needed for an in-app AI agent, including persistent conversations and document-based answers.

agent — Command by get-convex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add commands/get-convex/convex-agent-plugins/agent

Clone the repo

git clone --depth 1 https://github.com/get-convex/convex-agent-plugins

Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 389 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00021	$0.00389
Opus 5	$0.00010	$0.00195
Sonnet 5	$0.00004	$0.00078
Haiku 4.5	$0.00002	$0.00039

Measured 2d ago against content hash 67e6bc46106f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

commands/agent.md · 21 lines

What it actually says

Add an AI agent / RAG backend

Install @convex-dev/agent for durable threads, message history, tool-calls, and vector search/RAG — the backend for an in-app AI agent. Call models through the Convex AI Gateway by default: Convex holds the provider credentials, so there is no LLM key to obtain, store, or rotate.

Steps

Install @convex-dev/agent + @convex-dev/ai-sdk-provider; add the agent component to convex.config.ts.
Define the agent (tools, instructions) with languageModel: convexGateway("provider/model") — no API key needed (needs convex 1.45+ on a Convex Cloud deployment, paid plan).
Create threads + stream messages; persist history in Convex.
For RAG: embed docs into a vector index and retrieve in the tool. The gateway does not serve embeddings yet, so store the embedding provider's key via the env micro power.
Only if the gateway is unavailable (free plan, self-hosted, local backend): call the provider SDK with a key stored via the env micro power.

Rules

Default to the Convex AI Gateway (convexGateway from @convex-dev/ai-sdk-provider) for model calls; fall back to a provider key in Convex env only where the gateway is unavailable (free plan, self-hosted, local backend).
Never expose a provider API key client-side; when one is needed (embeddings, gateway fallback), keep it in Convex env via the env micro power.
Run model calls in actions ('use node' if the SDK needs it).
Persist threads/messages in Convex for durability + reactivity.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 21 lines · 21 tokens per session scan A 67e6bc46106f

Subscribe to this mod's changes

agent is a command published in the GitHub repository get-convex/convex-agent-plugins (112 stars, last pushed 4d ago), licensed MIT. It adds 21 tokens to every session and 389 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Building agents Data and AI RAG and vectors

agent

Getting it into your agent

What it costs to keep this loaded

Grade A, and why

Nothing flagged

What it actually says

Add an AI agent / RAG backend

Steps

Rules

What this file has done since we first saw it

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