# Quickstart

> Index of the TerraLab docs for agents: [llms.txt](https://terra-lab.ai/docs/llms.txt). Every docs page is also served as markdown: add .md to its URL.

Two paths: call the REST API from code, or add the MCP server to an AI agent. Both use the same account and the same 100 free calls a month.

## Call the API from code

### Create an API key

1. Sign in at [terra-lab.ai/login](https://terra-lab.ai/login). An account is free and needs no card.
2. Open [Dashboard, MCP](https://terra-lab.ai/dashboard/mcp), then **Advanced**, **API keys**.
3. Name the key, accept the API terms and click **Create key**.
4. Copy the key now: it starts with `tlk_` and is shown only once.

Keep it in an environment variable, never in your code:

```bash
export TERRALAB_API_KEY="tlk_your_key_here"
```

### Check the key

`GET /v1/me` returns your account and the calls you have left this month.

```bash
curl https://mcp.terra-lab.ai/v1/me \
  -H "Authorization: Bearer $TERRALAB_API_KEY"
```

A `401` means the key is missing, mistyped or revoked.

### Make your first tool call

Find the coordinates of an address with `find_places`:

```bash
curl -X POST https://mcp.terra-lab.ai/v1/tools/find_places \
  -H "Authorization: Bearer $TERRALAB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query":"12 rue de la Paix, Annecy"}'
```

```python
import os
import requests

response = requests.post(
    "https://mcp.terra-lab.ai/v1/tools/find_places",
    headers={"Authorization": f"Bearer {os.environ['TERRALAB_API_KEY']}"},
    json={"query": "12 rue de la Paix, Annecy"},
    timeout=120,
)
response.raise_for_status()
print(response.json()["structuredContent"])
```

```javascript
const response = await fetch('https://mcp.terra-lab.ai/v1/tools/find_places', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.TERRALAB_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({ query: '12 rue de la Paix, Annecy' }),
});
const data = await response.json();
console.log(data.structuredContent);
```

The answer is a JSON object: `structuredContent` holds the result with its `sources`, `content` the same result as text, and `isError` says whether the tool refused the request.

### Go further

- Extract buildings and roads for an area with [extract_open_data](https://terra-lab.ai/docs/api/extract_open_data).
- Get elevation, a profile or contour lines with [get_elevation](https://terra-lab.ai/docs/api/get_elevation).
- Browse all 29 tools in the [API reference](https://terra-lab.ai/docs/api).

## Add TerraLab to an AI agent

In Claude Code, one command:

```bash
claude mcp add --transport http terralab https://mcp.terra-lab.ai/mcp
```

Then run `/mcp` in Claude Code and sign in to TerraLab. For Claude, ChatGPT, Cursor, Codex and VS Code, see [MCP server](https://terra-lab.ai/docs/mcp).

Ask, for example: "Show the buildings within 500 m of Lyon Part-Dieu station and give me a GeoPackage."

Source: https://terra-lab.ai/docs/quickstart · Updated 2026-10-27