Social media API responses fill the AI's context and burn tokens: what to do
Use an API whose answers are clean, then ask only for the fields you need. What an AI reads through DataXAPI takes 95% fewer tokens than the platform's raw JSON; with view: "compact", a page of 20 Douyin comments is 2,996 tokens. The free trial covers up to 333 calls; a failed call is not charged.
Updated 2026-11-06
Why does it fill up?
Many data APIs pass the platform's raw JSON on as it is. That is the shape the platform uses for its own screens, with dozens of unused fields on every item. A page of 30 TikTok search results is 919k tokens raw, more than most models' context window: the AI cannot read it all, and cuts it or fails.
Four things to do
Biggest effect first.
| What | How | Effect |
|---|---|---|
| A clean answer | Read it through DataXAPI's MCP server | That TikTok page comes to 5,767 tokens |
| Core fields only, on a direct call | view: "compact" | The JSON comes to 5,963 tokens |
| Name the fields | fields: ["text", "metrics.likes"] | Only those come back |
| Fewer items, page by page | limit where a list endpoint takes it, page.next_cursor for the next | One page in context at a time |
What is clean about DataXAPI's answers?
Only the fields defined: each endpoint's page lists them one by one, and what the platform sends for its own screens (styling, tracking, the same image in several sizes) is left out.
One set of names on every platform: the author in author, likes, comments and plays in metrics, the time in published_at as ISO 8601 UTC, the next page in page.next_cursor. From Douyin to Xiaohongshu, the AI has no new structure to work out.
What the platform does not give is said: meta.unavailable lists the fields missing and why, so the AI does not read a missing value as 0.
How does it work through MCP?
Once connected, the AI can pass view and fields with call itself. An answer too long is cut, and the AI is told; read_more reads the rest for free. A result is kept for 24 hours and can be read again by its request ID, in another view, at no charge.
To connect: paste this to your AI assistant: “Read https://dataxapi.com/agents.md and set up DataXAPI here. My API key is dx_…; use it for every DataXAPI call.” A client that takes a remote MCP server can be given https://api.dataxapi.com/mcp with the header Authorization: Bearer <key> instead.
Where do these figures come from?
How it was counted: one recorded real response a endpoint (the one on its page). The raw JSON is the platform's answer as it came; DataXAPI's JSON is the default answer of a direct API call, meta and billing included; what an AI reads is the text the MCP server gives the model (the compact view, its first line included). Counted with GPT-4o's o200k tokenizer on 2026-11-06. A few endpoints that answer with a handful of numbers (read counts, transcripts) come out tens to hundreds of tokens larger, with the common envelope added.
| One call | Items | Platform's raw JSON | DataXAPI JSON | What an AI reads (MCP) | AI reads fewer |
|---|---|---|---|---|---|
| Douyin video search | 7 | 187k | 2,329 | 1,622 | 99% |
| TikTok video search | 30 | 919k | 11k | 5,767 | 99% |
| Weibo search | 9 | 145k | 2,715 | 1,530 | 99% |
| Kuaishou video search | 10 | 100k | 2,248 | 1,521 | 98% |
| Xiaohongshu note search | 15 | 51k | 10k | 3,600 | 93% |
| Douyin video comments | 20 | 23k | 4,403 | 2,978 | 87% |
| Xiaohongshu note details | 1 | 9,619 | 1,442 | 417 | 96% |
| WeChat article text | 1 | 7,198 | 949 | 686 | 90% |
| WeChat Channels video search | 10 | 8,252 | 2,668 | 1,476 | 82% |
| Bilibili video search | 20 | 10k | 4,576 | 3,325 | 67% |
Why DataXAPI
- Steady: endpoints were available 99.9% of the last 30 days, on a public status page you can check.
- Fast: a paid call took 2.5 seconds at the median over the last 7 days (counted 2026-11-06).
- Fewer tokens: across 226 endpoints, one recorded real response each, the platform's own JSON comes to 9.2M tokens and what an AI reads through DataXAPI's MCP server to 452k, 95% fewer; the JSON of a direct API call is 90% fewer too (counted 2026-11-06). Every platform answers in one shape: the author in
author, counts inmetrics, the next page inpage.next_cursor, so another platform needs no new parser. - See before you pay: every endpoint's page shows a recorded real response, field by field.
- Spending you control: a failed call is not charged; each key can have a limit,
X-Max-Pricecaps one call, and the sameIdempotency-Keywithin 24 hours is never charged twice. - Ready for AI: a remote MCP server listed in the official MCP registry as
com.dataxapi/mcp, usable from Claude, Cursor and ChatGPT. - Free trial of up to 333 calls, no card.
Endpoints
Each with its price; every page has the parameters, the fields and a recorded response.
Start with one key.
230 endpoints on 21 platforms, from $0.0003 a call. Errors and timeouts are not charged.