Use case
Instagram Data API for AI Agents — MCP Servers, Tool Schemas and Token Cost
An agent needs three things from a data API: a machine-readable contract, a single auth header, and errors it can reason about. All three are here by default.
The problem
social media API for AI agents: the problem.
Most APIs force you to hand-write tool definitions, then maintain them as the API drifts. An agent calling an undocumented endpoint with an unpredictable error shape will retry a terminal lookup outcome forever and burn your budget doing it.
The recipe
Endpoint workflow for social media API for AI agents.
The useful part of a use-case page is the translation from situation to endpoint. Here it is.
- 01Discovery without hand-written toolsThe full catalogue is generated from the same source of truth the API routes use, so the spec can never drift from what the endpoints actually accept. Point your agent framework at it and the tools define themselves.OpenAPI spec
- 02Context without scraping your own docsA plain-text summary of every endpoint, the auth model, the envelope and the error codes — sized for a context window rather than for a browser.llms.txt
- 03Auth an agent can holdOne header, no refresh cycle, no OAuth callback. Nothing in the auth path requires a human to be present, which is the point.One API key
- 04Errors an agent can act onEvery error says what happened and whether you were charged. A data.profile=null result means stop, a 500 can be retried with backoff, and a 402 means top up — unambiguous enough that a model gets it right without prompt engineering.Consistent error model
Budget
Credit estimate for social media API for AI agents.
Agents are bursty and repetitive, so put a small queue in front of them and sum credits_charged across the run. That is the exact spend, even when the agent retries.
See pricingFAQ
social media API for AI agents FAQ.
Is there an MCP server?
Not today, and none is promised. The OpenAPI document at /openapi.json is what an agent framework needs to generate tool definitions, and llms.txt describes the whole contract in plain text — both are generated from the same catalogue the API serves, so neither can drift out of date.
How do I stop an agent burning credits?
Issue it a dedicated API key, then watch that key in request history. Per-key spend is visible and a key can be revoked instantly.
Can an agent discover new endpoints automatically?
Yes — the spec is generated from the catalogue, so anything we ship appears there the moment it goes live, with no action from you.