# mastodon.timeline_tag

**stable** **Advanced**

Public posts for a hashtag.

`GET /v1/mastodon/timeline_tag`

## What you get

A list of Mastodon results in Onekey's unified shape, in `data` (an array). An empty array is a normal, successful answer and is charged like any other; a source that reports "nothing found" as an error returns a free `404 not_found` instead.

## What it costs

- **Advanced · 5 credits** for a fresh fetch, charged only when it succeeds.
- **Free when served from cache (0.2 credit for a cached response over 100 KB).**
- **Free** if the request is invalid (never charged) or the source fails or reports not found (refunded).

## Parameters

| Name | Type | Required | Default | What it is | Constraints |
| --- | --- | --- | --- | --- | --- |
| `instance` | string | no | - | Known Mastodon instance (allowlisted), default mastodon.social | max 253 chars; must match `[a-z0-9.-]{3,253}`; trimmed, lowercased |
| `tag` | string | yes | (required) | Hashtag without #, e.g. python | max 100 chars; must match `[A-Za-z0-9_]{1,100}`; trimmed, lowercased |

## Request

```bash
curl "https://api.onekey.dev/v1/mastodon/timeline_tag?tag=python" \
  -H "x-api-key: YOUR_API_KEY"
```

```python
import requests

res = requests.get(
    "https://api.onekey.dev/v1/mastodon/timeline_tag",
    params={"tag": "python"},
    headers={"x-api-key": "YOUR_API_KEY"},
)
body = res.json()

if body["success"]:
    print(body["data"])
else:
    print(body["error"]["code"], body["error"]["message"])
```

```javascript
const params = new URLSearchParams({ tag: "python" });
const res = await fetch(`https://api.onekey.dev/v1/mastodon/timeline_tag?${params}`, {
  headers: { "x-api-key": "YOUR_API_KEY" },
});
const body = await res.json();

if (body.success) console.log(body.data);
else console.error(body.error.code, body.error.message);
```

## Recorded response

A real Mastodon response, recorded and returned in Onekey's shape. Fields the platform does not provide are `null`.

```json
{
  "success": true,
  "data": [
    {
      "content": {
        "id": "117350344281766094",
        "url": "https://www.urbanmind.net/display/f7dd981d-cec99446-d49183579dfadbe9",
        "text": "I originally thought customer memory was a storage problem. It turned out to be a retrieval and trust problem. When I built FUEGO, a customer relationship memory agent, I wanted one simple behaviour: before a customer meeting, the system should remember what happened before without forcing someone to reconstruct the relationship from scattered meetings, tickets, and notes. The key design decision was separating structured customer records from long-term semantic memory. SQLite remains the source of truth for customers, meetings, and support tickets. Hindsight handles the historical context that needs to be retrieved when a question is asked. Groq then turns that context into a useful response. That separation made the rest of the system much easier to reason about. The architecture: FUEGO uses a Next.js frontend and a Python/FastAPI backend. The frontend lets a user select a customer, add meetings and support tickets, prepare for a meeting, inspect commitments and solutions, and ask questions. The backend connects SQLite, Hindsight, and Groq. SQLite stores concrete records. Hindsight provides long-term customer context. Groq uses the retrieved context to generate the final response. I wanted those responsibilities to stay separate. A database row is not the same thing as a memory, and a retrieved memory is not automatically a fact that should overwrite a structured record. Why ordinary customer history",
        "createdAt": "2026-09-28T19:06:23Z",
        "language": "en"
      },
      "author": {
        "id": "115061140460610278",
        "username": "hackaday",
        "displayName": "Hack a Day (unofficial)",
        "url": "https://www.urbanmind.net/profile/hackaday",
        "avatarUrl": "https://files.mastodon.social/cache/accounts/avatars/115/061/140/460/610/278/original/b7c7093473e2d110.png"
      },
      "engagement": {
        "likes": 0,
        "comments": 0,
        "shares": 3
      }
    },
    {
      "content": {
        "id": "117350295913913001",
        "url": "https://mastodon.social/@teeeeeeeee/117350295913913001",
        "text": "Boosted Configuration (_neural_) Networks for classification https:// thierrymoudiki.github.io/blog/ 2022/07/21/r/misc/boosted-configuration-networks # Python # DataScience # MachineLearning # rstats # Techtonique",
        "createdAt": "2026-09-28T19:23:31Z",
        "language": "en"
      },
      "author": {
        "id": "116862964066274332",
        "username": "teeeeeeeee",
        "displayName": "T@Techtonique",
        "url": "https://mastodon.social/@teeeeeeeee",
        "avatarUrl": "https://files.mastodon.social/accounts/avatars/116/862/964/066/274/332/original/7b6c651c404d5235.png"
      },
      "engagement": {
        "likes": 0,
        "comments": 0,
        "shares": 2
      }
    }
  ],
  "metadata": {
    "platform": "mastodon",
    "endpoint": "timeline_tag",
    "cached": false,
    "stale": false,
    "age_s": 0,
    "fetched_at": "2026-01-01T12:00:00+00:00",
    "credits_charged": 5,
    "request_id": "7f3a9c2e5b1d4c8fa2e6d0b9c4f18e37"
  },
  "error": null
}
```

## Field mapping

How this endpoint's source fields become Onekey's [unified schema](https://onekey.dev/docs/schema.md). Fields the source lacks come back as `null`.

| Source path | Onekey field | Transform |
| --- | --- | --- |
| `id` | `content.id` | - |
| `url` | `content.url` | `safeUrl` |
| `content` | `content.text` | `stripHtml` |
| `created_at` | `content.createdAt` | `toIsoDate` |
| `language` | `content.language` | - |
| `account.id` | `author.id` | - |
| `account.username` | `author.username` | - |
| `account.display_name` | `author.displayName` | - |
| `account.url` | `author.url` | `safeUrl` |
| `account.avatar` | `author.avatarUrl` | `safeUrl` |
| `favourites_count` | `engagement.likes` | `toNumber` |
| `replies_count` | `engagement.comments` | `toNumber` |
| `reblogs_count` | `engagement.shares` | `toNumber` |

## Caching and freshness

- Fresh for about 30 seconds. Repeat calls in that window are served from cache and are free.
- Between 30 seconds and 5 minutes the cached copy is still served instantly and marked `stale: true` while Onekey refreshes it in the background.
- If the source is down when a refresh is needed, the last copy can be served for up to 1 hour more (marked stale).
- A "not found" is remembered for 1 minute and is free.
- The cache is shared across all customers, which is what keeps repeat calls cheap.

## What can go wrong

| Status | Code | What to do |
| --- | --- | --- |
| 401 | `unauthorized` | Check the `x-api-key` header. |
| 402 | `insufficient_credits` | [Add credits](https://onekey.dev/pricing); your balance must cover the price. |
| 404 | `not_found` | Unknown endpoint path. |
| 422 | `invalid_params` | Fix the parameters using the table above. Free. |
| 429 | `rate_limited` | Wait `Retry-After` seconds, then retry. |
| 502 | `upstream_error` | The source failed. Refunded; retry with backoff. |

See [Errors](https://onekey.dev/docs/errors.md) for the full list and retry guidance.

Status: stable (verified against the live source).