> ## Documentation Index
> Fetch the complete documentation index at: https://agenthook.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Using from Claude Code & Cursor

> Hand the CLI to your coding agent — it's built for this.

AgentHook is designed to be driven by agents, not humans in a dashboard. **The CLI is the agent surface today**: any agent that can run shell commands (Claude Code, Cursor, Codex-style agents, n8n exec nodes) can generate media with it. An MCP server and an installable skill pack are coming later — both will be thin wrappers over the same API.

## Setup

Install and authenticate once on the machine your agent runs on:

```bash theme={null}
npm i -g getagenthook
agenthook login   # paste an API key from the console
```

(Keys are created in the [console](https://getagenthook.com) — see [Authentication](/authentication).)

## Tell your agent about it

Add a note to your project's agent instructions (`CLAUDE.md`, Cursor rules, etc.):

```markdown theme={null}
## Media generation

The `agenthook` CLI generates videos and images (real credits — don't run speculatively):

- `agenthook tools` — print every tool and its full input schema
- `agenthook run make_video --prompt "..."` — video; put spoken lines in the
  prompt ('She says: "..."'); flags: --captions, --enhance-prompt; with reference
  images, --owns-references is required (likeness consent)
- `agenthook run make_image --prompt "..."` — images (refs = editing)
- `agenthook run caption_video --video-url <url>` — burn in subtitles
- `agenthook list --search "<keywords>"` — find past generations before
  making new ones
- `agenthook balance` — check credits first

Runs print a durable media URL when done.
```

## Why this works well for agents

* **Self-describing schemas.** `agenthook tools` (backed by `GET /api/v1/tools`) prints every argument, type, default, and enum — the agent never has to guess or memorize the API.
* **Local pre-validation.** The CLI checks everything deterministically checkable — enum values, prompt length caps, references without the `owns_references` attestation — *before* any network call, and fails with a message the agent can read and self-correct from. No credits are spent on malformed requests.
* **Submit–poll handled for you.** `run` blocks until the media is ready and prints the URL — one command, one result, no polling loop for the agent to write.
* **Searchable memory.** `agenthook list --search "..."` full-text-searches past runs (prompt, enhanced prompt, transcript), so an agent can reuse yesterday's video instead of paying to regenerate it.

## No CLI? Use HTTP directly

Everything the CLI does is plain REST — agents that only speak HTTP can hit the API directly:

```bash theme={null}
curl -X POST https://getagenthook.com/api/v1/tools/make_image/run \
  -H "Authorization: Bearer $AGENTHOOK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Flat-lay of a lime-green running shoe on dark slate", "aspect_ratio": "1:1"}'
```

Then poll `GET /api/v1/runs/{run_id}` until `completed`. See the [Quickstart](/quickstart) for the full flow.

## Coming later

* **MCP server** — the same three tools over the Model Context Protocol, for MCP-native clients.
* **Skill pack** — installable agent skills that wrap the CLI with usage guidance.

Both will read their schemas from `GET /api/v1/tools`, same as the CLI — one schema source, no drift.