Why this subject deserves an implementation guide
The starting question for this article came from a public Context.dev post titled "1st party vs 3rd party data — a developer's guide". Rather than reproduce that article, this guide asks what the same product problem looks like inside MediaHarvester and what can be verified in the running application.
Brand information is scattered across metadata, assets, stylesheets and page links. Collecting it manually makes otherwise small product features costly to maintain.
The MediaHarvester approach
MediaHarvester normalizes brand details from accessible website sources and exposes simplified or full responses depending on the UI need. Rich extraction can add fonts, styleguide tokens, screenshots and classifications.
The primary surface for this workflow is `GET /v1/brand/retrieve`. It can be tried from the API playground and integrated through the local API key, SDK, CLI or MCP layer.
Workflow map
A realistic application scenario
A software team needs company identity data for account pages, internal tools and generated reports.
The workflow begins with a narrowly scoped public or authorized source, records the endpoint output and makes the result reviewable before it becomes visible to users or informs an automated decision.
Try the capability
GET /v1/brand/retrieve Local API key:mh-localhost-dev-key
GET /v1/brand/retrieve?domain=web-tasarimci.comImplementation choices that matter
Prefer simplified retrieval for lists and autocomplete, then request richer data only on detail pages or generation jobs. Cache stable results, expose refresh controls and always keep source domains visible.
This matters because a production feature is judged less by a perfect demo result than by how it behaves when an asset is missing, a source changes, a response is cached or a request is not allowed.
How to measure whether it works
Monitor cache hit rate, field availability, refresh time, asset fallback frequency and the user actions that become possible once context is available.
The app should retain enough source and request metadata to debug poor results while applying appropriate retention and access policies for customer data.
A responsible next step
Run the included endpoint against a website you control or are authorized to process, inspect the response in Visual and JSON modes, then decide which fields deserve automation and which deserve human approval.
MediaHarvester deliberately treats blocked, verification-required, login-required, robots-disallowed and permission-required outcomes as information, not obstacles to be bypassed.
FAQ
Questions teams ask before implementing this workflow
What does this web context workflow return?
It uses GET /v1/brand/retrieve and related MediaHarvester surfaces to return structured context together with metadata appropriate to the workflow.
Can I test this locally?
Yes. Run the local service at http://127.0.0.1:8013 and send X-API-Key: mh-localhost-dev-key to protected API routes.
Does it work with private or blocked pages?
The platform is designed for publicly accessible or authorized sources. Verification, login, permission and robots restrictions are reported rather than bypassed.
Can this be automated?
The same API surfaces are available through CLI, Python and TypeScript SDKs, MCP tools and starter no-code integration templates.
How do I keep the result current?
Use cache freshness controls such as maxAgeMs where exposed, and schedule refreshes in a production worker only as frequently as the business case needs.