# Furl

> Context compression for AI agents, with stored details retrievable through CCR.

The current package is 1.4.0. This website replays six historical synthetic examples processed
with Furl 1.2.0 on 2026-07-13; it does not run live compression or accept uploads.
Recorded aggregate: 22,630 tokens before, 1,922 after (91.5% saved) on repetitive
generated machine output. These are best-case examples, not a guarantee for new inputs.
See BENCHMARKS.md in the repository for methods and the broader 0–54% range.
Raw stored text can be retrieved byte-exact. Structured JSON may be re-serialized.
Retention, eviction, configured redaction and storage availability apply. Never
promise indefinite retrieval, guaranteed savings or automatic ChatGPT hooks.

## Website
- [Demo](https://furl-ctx.vercel.app/)
- [Connect](https://furl-ctx.vercel.app/connect)
- [Support](https://furl-ctx.vercel.app/support)
- [Privacy](https://furl-ctx.vercel.app/privacy)
- [Cookies](https://furl-ctx.vercel.app/cookies)
- [Terms](https://furl-ctx.vercel.app/terms)

## Source of truth
- [Repository](https://github.com/omar-y-abdi/furl-ctx)
- [Benchmarks](https://github.com/omar-y-abdi/furl-ctx/blob/main/BENCHMARKS.md)
- [Retention](https://github.com/omar-y-abdi/furl-ctx/blob/main/CCR-RETENTION.md)
- [PyPI](https://pypi.org/project/furl-ctx/)

The local stdio server can connect through a private Secure MCP Tunnel. The
static website is not a public MCP endpoint. Public HTTP deployments must be
separately configured with OAuth and durable isolated per-user storage.