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

# Quickstart

> Get started with Timepoint AI — render your first historical moment in minutes.

# Quickstart

## Hosted API — The Fastest Path

The hosted API at `api.timepointai.com` is the easiest way to use Timepoint. The Gateway handles authentication, credits, and proxies your requests to Flash and other services.

### Authenticate

Sign up through the [Timepoint app](https://app.timepointai.com) to get your credentials. The Gateway supports Apple, Google, and GitHub OAuth.

### Render a Moment

```bash theme={null}
curl -X POST https://api.timepointai.com/api/v1/timepoints/generate/sync \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -d '{"query": "AlphaGo plays Move 37, Seoul, March 10 2016", "generate_image": true}'
```

You'll get back a complete scene: characters with distinct voices, period-accurate dialog, relationship dynamics, source citations, and a photorealistic image.

### Query the Clockchain

The Clockchain is a public API — no authentication needed for read access.

```bash theme={null}
# Get graph statistics
curl https://clockchain.timepointai.com/api/v1/stats

# Search moments by keyword
curl "https://clockchain.timepointai.com/api/v1/moments?q=rome"
```

### Connect via MCP

The Clockchain exposes a [Model Context Protocol](https://modelcontextprotocol.io) endpoint for LLM tool use:

```
Endpoint: https://clockchain.timepointai.com/mcp/
Transport: Streamable HTTP (v1.26.0)
```

Point any MCP-compatible client (Claude Desktop, Cursor, etc.) at the endpoint to give your LLM direct access to the temporal causal graph.

***

## Local Development

The sections below cover running Timepoint services locally from source.

### Flash — Render a Historical Moment

Flash is a pure generation engine. In production, the Gateway handles auth and proxies requests to Flash. Locally, you can run it standalone.

#### Prerequisites

* Python 3.10+
* A Google API key ([free at AI Studio](https://aistudio.google.com))

#### Install and Run

```bash theme={null}
git clone https://github.com/timepointai/timepoint-flash.git
cd timepoint-flash
pip install -e .
```

Set your API key:

```bash theme={null}
export GOOGLE_API_KEY="your-key-here"
```

Start the server:

```bash theme={null}
flash serve
```

#### Render a Moment

```bash theme={null}
curl -X POST http://localhost:8000/api/v1/timepoints/generate/sync \
  -H "Content-Type: application/json" \
  -d '{"query": "AlphaGo plays Move 37, Seoul, March 10 2016", "generate_image": true}'
```

***

### Clockchain — Query the Graph Locally

See the [Hosted API](#hosted-api--the-fastest-path) section above for querying the public Clockchain. To run locally:

```bash theme={null}
git clone https://github.com/timepointai/timepoint-clockchain.git
cd timepoint-clockchain
```

Refer to the repository README for local setup instructions.

***

## Next Steps

<CardGroup cols={2}>
  <Card title="Core Concepts" icon="book" href="/concepts">
    Understand timepoints, SNAG, and temporal modes
  </Card>

  <Card title="Flash Deep Dive" icon="bolt" href="/products/flash">
    The 14-agent pipeline explained
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference/overview">
    Full endpoint documentation
  </Card>

  <Card title="Clockchain" icon="link" href="/products/clockchain">
    How the temporal graph works
  </Card>
</CardGroup>