XCrap: Public X Post Reader API

What is XCRAP: Public X Post Reader API?

XCRAP is a free service that allows users to retrieve public posts, threads, and profiles from X (formerly Twitter) in clean, structured formats such as Markdown, JSON, YAML, CSV, or HTML. It provides an easy way for developers, bots, and small projects to access public X data without requiring an API key or account, simplifying data extraction and integration.

Who is it for?

The service is designed for developers, researchers, and small project teams who need to read and process public X content efficiently. It benefits those building bots, data analysis tools, or integrations that require access to public posts, profiles, and threads without the overhead of API restrictions or costs.

How is it priced?

XCRAP is completely free, with no account registration, API key, or payment required. It is funded by donations and minimal hosting costs. Users can access the service without any charges or sign-up processes.

How does it compare to alternatives?

This service offers a keyless, free alternative to the official X API, focusing on simplicity and accessibility for small-scale projects. Unlike paid API plans that limit access or require subscriptions, XCRAP provides unrestricted public data retrieval in multiple formats, making it suitable for quick integrations and research workflows. It is ideal for those who need straightforward access without platform restrictions or costs.

Key features

• Reads public posts, threads, and profiles from X without requiring an account or API key
• Provides data in multiple formats including Markdown, JSON, YAML, CSV, and HTML
• Supports bulk retrieval of multiple posts or threads in a single request
• Streams media files such as images and videos directly, without storing them
• Offers an API compatible with various agents and bots for easy integration
• Includes search functionality for public X content with operator support

Use cases

Developers can embed public X posts into their applications or bots for display or analysis.

Researchers can extract and process large volumes of public data for studies or data science projects.

Small teams can automate content collection for monitoring or archiving purposes without API costs.