Thunderbit Developer API
Turn complex websites into structured data for RAG pipelines, AI agents, and LLM context windows. Web scraping rebuilt for the AI era.
Try It →
Turn complex websites into structured data for RAG pipelines, AI agents, and LLM context windows. Web scraping rebuilt for the AI era.
Try It →
Thunderbit's Developer API is built for engineers who are tired of writing brittle scrapers to feed their RAG pipelines. If you are building AI agents that need to ingest real-world web content, this is a serious contender: it handles the messy extraction layer so you can focus on what happens after the data arrives. The combination of a REST API, MCP server, and CLI gives you flexibility most scraping tools simply do not offer for AI-native workflows.
As of May 2026. Thunderbit has not published detailed public pricing tiers on this page.
Likely $0
TBD
Custom
Note: Thunderbit's public documentation does not list explicit pricing tiers at this time. The above is inferred from typical API product structures. Check their site for current details.
Point the API at any URL and get back clean, structured content. It handles JavaScript-heavy SPAs, paywalled layouts, and complex DOM structures that break traditional scrapers.
Every extraction returns both clean Markdown (ideal for LLM context windows) and structured JSON (ideal for database ingestion and RAG chunking). No post-processing scripts needed.
Ships with a Model Context Protocol server out of the box. This means AI agents built on Claude, GPT, or open-source models can call Thunderbit as a tool natively, without custom middleware.
The command-line tool lets you pipe web content directly into scripts, cron jobs, or CI/CD pipelines. Useful for batch extraction and local development without touching the REST API.
This is not a traditional scraping tool with AI bolted on. The output formats, chunking strategies, and integration patterns are designed specifically for feeding LLMs and retrieval-augmented generation systems.
Standard REST endpoints mean you can integrate Thunderbit into any stack. Python, Node, Go, whatever you are running. Authentication is API key-based, and responses are predictable and well-structured.
Strips navigation, ads, cookie banners, and boilerplate from extracted content. What you get back is the actual content of the page, not the wrapper around it. This matters when every token in your context window counts.
Designed to handle the sites that break other tools: dynamic rendering, infinite scroll, embedded iframes, and multi-page content. The extraction engine renders pages before parsing, catching content that static scrapers miss entirely.
If you are building retrieval-augmented generation systems and need a reliable way to ingest web content into your vector store, Thunderbit replaces the fragile scraping layer. The structured JSON output maps cleanly to embedding workflows.
Building agents that need to browse and understand the web? The MCP server integration means your agent can call Thunderbit as a tool, get clean content back, and reason over it. No screen scraping hacks required.
Need to systematically extract and analyze content from competitor sites, industry publications, or regulatory pages? The CLI makes batch extraction straightforward, and the Markdown output is immediately readable by both humans and LLMs.
If your product needs to summarize web pages, answer questions about URLs, or ground LLM responses in real web content, Thunderbit handles the extraction so you can focus on the intelligence layer above it.
Thunderbit's Developer API is purpose-built for the extraction layer your RAG pipeline has been missing.
Try Thunderbit Developer API →