Task-specific APIs for common platforms
Mindcase provides prebuilt APIs for platforms including LinkedIn, Google Maps, Amazon, Instagram, Reddit, and X, with separate endpoints for different data extraction tasks.
Mindcase provides web data APIs and prompt-based access to extract structured data from LinkedIn, Google Maps, Amazon, Instagram, Reddit, and more. Teams and agents can collect analysis-ready records using prebuilt scrapers, API runs, and MCP connectivity.
Mindcase is a web data platform that returns structured records from public websites and online platforms. It is organized around prebuilt APIs for specific tasks, so users can request data such as profiles, places, reviews, posts, or company records without building their own scrapers.
The product is aimed at developers, AI agents, and enterprise teams that need analysis-ready data from multiple web sources. The site shows workflows for running jobs through an API, using a console or prompt, and connecting through MCP, with results returned as structured JSON rows.
Mindcase provides prebuilt APIs for platforms including LinkedIn, Google Maps, Amazon, Instagram, Reddit, and X, with separate endpoints for different data extraction tasks.
The platform returns clean, analysis-ready records instead of raw page data, which makes the output easier to store, filter, and process in downstream systems.
The skills file describes a job-based process: start a run, poll for completion, and then read the resulting rows from the completed response.
The homepage references multiple ways to use the product, including a console, copy-paste prompts, and MCP connectivity for agents and connected tools.
Pricing is based on the records returned rather than seats or fixed plans. Credits are prepaid, billed from a wallet, and do not expire.
The company says it can build and run custom data sources, complex pipelines, or fully managed runs for customers that need something beyond the catalog.
Teams building agents can connect to Mindcase to fetch structured records from specific sources instead of writing scraper logic inside the agent.
Enterprise teams can use platform data such as reviews, company profiles, places, and social posts to assemble datasets for research and monitoring.
The LinkedIn APIs shown on the site support profile, company, employee, and post data, which can be used to enrich prospecting or account research workflows.
Amazon reviews, Google Maps places, and social post APIs can support monitoring of product feedback, business listings, and public engagement signals.
For teams with unusual sources or multi-step pipelines, Mindcase offers custom data source builds and managed runs rather than only self-serve endpoints.
Mindcase runs jobs asynchronously. You start a run for a specific API task, then poll for completion and receive structured rows in the results response.
The site shows coverage for LinkedIn, Google Maps, Amazon, Instagram, Reddit, X, and other public web sources, with additional platforms mentioned in the skills file.
The pricing page says there are no plans or seats. Customers pay from wallet credit for the data they get, and credits do not expire.
Yes. The enterprise page describes proof-of-concept deployments, recurring intelligence workflows, and large-scale external data access for organizations.
Yes. The site says the team can build and run custom data sources, complex pipelines, or fully managed runs when the catalog does not cover the need.
Traffic data is for reference only.
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