WEB DATA & EXTRACTION · FOR AI AGENTS
Scrapfly
Fetch live web content through managed scraping, browser and extraction tools.
Connect an agent to Scrapfly’s hosted MCP server or APIs to retrieve pages, capture screenshots and extract structured data using managed browser and proxy infrastructure.
Your integration checklist
- Capabilities
- What you need from your owner
- Create a Scrapfly account and project, obtain credentials or authorize the MCP connection, and choose the credit plan and project access settings for the workload.
- Authentication
- The hosted MCP endpoint https://mcp.scrapfly.io/mcp supports OAuth2 or an Authorization bearer API key. Prefer these to putting a key in the URL. Check project IP restrictions against the actual calling client.
- Your first task
- Inspect account usage, then fetch one permitted page with the minimum required rendering options and validate the returned content.
- Billing & payment
- Operations consume credits according to configuration, including rendering and proxy choices. Plans provide quotas and concurrency; some paid plans allow usage-based overflow, so an allowance is not necessarily a spending cap.
- Agent payment support
- Not verified. Programmatic usage does not establish autonomous checkout support.
- Operational limits
- Sites can still block requests or return incomplete content. Quota, concurrency and timeout errors require separate handling. Browser rendering and proxy choices affect credit consumption; HTTP success alone does not establish useful extraction.
ORIGINAL AI AGENT STORE INTEGRATION PLAYBOOK
Validate page identity and extraction completeness before scaling retrieval
Editorial recommendation · Reviewed 2026-10-23
When to choose this service
Choose Scrapfly when an agent needs fresh web content served through operated scraping and browser infrastructure, with structured results it can validate against the requested page.
Maintained proxy capacity, running browsers and managed retrieval infrastructure provide resources beyond writing a parser. The integration still needs permission to access the target and checks for incomplete results.
Suggested workflow
- Define the permitted URL scope and required fields. Inspect credits and concurrency, then start with the least expensive configuration that retrieves the target content.
- Check the final page identity, required fields and evidence of an access challenge. Compare a representative extraction with the visible source before expanding the crawl.
- Bound concurrency and retries, record per-job usage and retain retrieval timestamps. Stop when the expected data is absent rather than treating an empty result as a fact.
Acceptance checks before real work
- Reject login, challenge and error pages that happen to return HTTP 200.
- Check required fields and pagination before calling a dataset complete.
- Inspect overflow billing settings alongside the nominal credit allowance.
If the workflow fails
Classify the error as access, quota, concurrency or timeout before retrying. Reduce parallelism for concurrency errors and stop at the job budget; avoid repeatedly paying for the same unusable page.