Headroom alternative that cuts the token bill: CrawlGenie
Headroom is an open-source library and proxy (Apache 2.0) that shrinks what an agent already holds, such as tool output, database rows, logs and retrieved chunks, before it reaches the model, and can fetch the original back on demand. CrawlGenie is a hosted web platform for AI agents: it reads less from the live web in the first place (passages, rows and snapshots instead of pages) and includes Compress, the same kind of code-only shrinking, for content you already have. Facts about Headroom were read from headroomlabs.ai and its GitHub README on 2026-10-13.
What is the difference between Headroom and CrawlGenie?
They solve different halves of the token bill. Headroom works after a tool has already returned a large result: it compresses that result (its README reports about 20% fewer tokens for coding agents and 60–95% for repeated JSON, with originals retrievable). CrawlGenie works before: web_answer, web_research and the extractors return only the passages, rows or snapshot lines that answer, so the large result never exists (98% fewer tokens on a live article, 88% on a four-source research question, both measured). For content you already have, CrawlGenie's Compress does what Headroom does for JSON and logs (85% and 89% in our measurements) as an API call or a connector tool, with the saving added to your Token savings page. Headroom has no browser, search, reading, extraction, monitoring or memory; CrawlGenie does not compress your conversation history or route between models.
| Capability | Headroom | CrawlGenie |
|---|---|---|
| What it is | Open-source library + local proxy + MCP server that compresses context (Apache 2.0); paid Enterprise tier | Hosted web platform for agents: browser, search, read, agents, monitor, memory, plus Compress; private deployment on the enterprise plan |
| Where the saving happens | After a tool returns a large result: the result is compressed before the model sees it | Before: only the passages, rows or snapshot lines that answer are returned; Compress covers content you already have |
| Reported savings | About 20% for coding agents, 60–95% for repeated JSON (vendor README, offline benchmark) | 98% on a live article, 88% on a 4-source research question, 85% on API JSON and 89% on logs via Compress (measured; the number is printed on every call) |
| Reading the live web | No (works on what your other tools fetched) | Pages, PDFs, Office files, search with sources and dates, 61 code-only extractors |
| Browser, logins, approvals | No | Real sessions, saved logins, approvals before pay/send/delete, take-over e-mail |
| Monitoring and memory | No | Watches with diffs and alerts; a knowledge store you can search for a few hundred tokens |
| Conversation history compression | Yes, reversible (originals retrievable on demand) | No: content you pass to Compress is shrunk, not the conversation itself |
| Model routing and prompt-injection checks | Enterprise tier | No |
| How you use it | SDK (Python, TypeScript), local proxy, CLI wrapper, MCP server | REST API and SDKs, MCP connector for Claude, ChatGPT and Perplexity, dashboard |
| Pricing | Open source free; Enterprise priced on request | Free, Pro $29, Team $99 a month, flat; Compress counts as a read |
Can you use both?
Yes, and many teams will. Headroom sits between your agent and the model; CrawlGenie sits between your agent and the web. The web side is where most of the tokens come from in research, sales and support agents, because every page read in full is tens of thousands of tokens; the model side matters most for long coding sessions. Neither replaces the other.
When should you stay with Headroom?
Stay with Headroom if you run a coding agent locally and want a transparent proxy in front of your model provider, if you need its reversible compression of conversation history, or if you want to self-host a compression layer under an open licence.
How do I migrate?
Nothing to migrate: the two can run together. Point your agent at CrawlGenie for the web and keep Headroom in front of the model if you use it. If you only want the compression part as a service, send the content to POST /v1/compress or call the compress connector tool.
For developers: the exact call
# Headroom (local, Python/TypeScript SDK or proxy) compressed = headroom.compress(messages) # CrawlGenie (hosted; the same idea for content you already have) POST https://crawlgenie.com/v1/compress {"content": "", "kind": "auto"} → content (smaller), tokensIn, tokens, savedPct # and for the web, read less in the first place POST https://crawlgenie.com/v1/scrape {"url": "...", "q": "refund policy"}
Related: web scraping for LLMs · MCP web browser · extractor library · free SEO + AIO report.
What would this save you?
Move the sliders. The saving is computed from the measured ratios above and the model price you pick.
List input prices on Oct 14, 2026: Claude Sonnet 5.5 and GPT-6.1 Sol $2, Gemini 4 Argon $2, Claude Opus 5.5 $4, Claude Fable 5.1 and GPT-6 Astra $10, Gemini 3.8 Flash $0.75, Claude Haiku 5.5 and GPT-6 Luna $0.10.
Assumes 10% of the page is kept per read (measured on 7 long pages: 2–10%). Token savings in the product show the real number for your traffic.
Questions people ask
Is Headroom free?
The library, proxy and MCP server are open source under Apache 2.0. Headroom Enterprise (model routing, prompt-injection checks, managed or VPC deployment, SSO) is priced on request. CrawlGenie plans are flat: Free, Pro $29 and Team $99 a month.
Does CrawlGenie compress like Headroom?
For content you already have, yes: POST /v1/compress and the compress connector tool turn repeated JSON into tables, group log lines and drop duplicates with no model, 85% smaller on API JSON and 89% on logs in our measurements. CrawlGenie does not compress your conversation history.
Which saves more tokens?
It depends on where your tokens go. If your agent reads the web, CrawlGenie removes the large result before it exists (98% on a live article, measured). If your agent mostly handles tool output from other systems, Headroom's compression applies to that. The two can run together.
Does either one change the answers?
Both keep the facts: CrawlGenie returns the original passages with their source, and its Compress never summarises, it only removes repetition; Headroom's README reports unchanged accuracy on its benchmarks and keeps originals retrievable.
Spend tokens on answers, not on pages.
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