Web reading layer for AI agents. Convert any public URL into structured intelligence — entities, business intent, confidence score — in one API call.
Scanned 9/9/2026
Install to Claude Code
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---
name: project-ghost
version: 2.0.0
description: Web reading layer for AI agents. Convert any public URL into structured intelligence — entities, business intent, confidence score — in one API call.
tags: [web, scraping, research, intelligence, agents, api, data-extraction]
author: Sid890-cpu
homepage: https://project-ghost-lilac.vercel.app
repository: https://github.com/Sid890-cpu/project-ghost
license: MIT
runtime:
env:
- name: GHOST_API_KEY
description: Your Ghost API key. Get one free at project-ghost-lilac.vercel.app
required: true
secret: true
---
# Project Ghost
Web reading layer for AI agents. Convert any public URL into structured, agent-ready intelligence in one API call.
## What it does
Feed Ghost any public URL and get back:
- **Business intent** — a 1-2 sentence summary of what the page is about
- **Named entities** — companies, people, products mentioned
- **Confidence score** — how reliable the extraction is (0-1)
- **Tokens saved** — how much token reduction vs raw HTML (avg 80%+)
- **Priority score** — relevance signal (1-10)
## Usage
```
Read this page and tell me what it's about: https://openai.com
```
```
Research Stripe's latest products using Ghost
```
```
What are the top stories on Hacker News right now?
```
## How to use in your agent
Set your `GHOST_API_KEY` environment variable, then call:
```bash
curl -X POST https://project-ghost-production.up.railway.app/distill \
-H "Authorization: Bearer $GHOST_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url": "https://apple.com"}'
```
## Response format
```json
{
"title": "Apple",
"tokens_saved": "80.7%",
"signals_data": {
"decision_signal": {
"business_intent": "Apple promotes its latest hardware lineup...",
"priority_score": 8,
"category": "Technology"
},
"items": [
{
"title": "MacBook Pro with M5",
"entities": ["Apple", "MacBook", "M5"],
"impact_score": 9
}
],
"integrity_layer": {
"confidence_score": 0.87,
"is_high_integrity": true
}
}
}
```
## Works great with
- Research agents reading company websites
- News monitoring agents tracking topics
- Sales agents detecting buying signals
- Legal agents extracting policy terms
- Any agent that needs to understand web content
## Sites that work
Most public websites work — Wikipedia, GitHub, HackerNews, OpenAI, Stripe, Apple, Anthropic, and thousands more.
Sites with enterprise Cloudflare protection (WSJ, FT, Nike) may be blocked — the API returns a clear blocked message in that case.
## Get your free API key
Visit **project-ghost-lilac.vercel.app** → enter your email → get an instant `ghost_sk_...` key.
Free plan: 100 requests/month. No credit card needed.
## Links
- Homepage: https://project-ghost-lilac.vercel.app
- API Docs: https://project-ghost-production.up.railway.app
- GitHub: https://github.com/Sid890-cpu/project-ghost
- Integration Guide: https://project-ghost-lilac.vercel.app/integrate.html
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