Lightpaper Mcp

org.lightpaper由 lightpaper.org 发布v0.1.1更新于 Oct 27, 2026

API-first publishing platform. Publish markdown as permanent web pages with quality scoring.

概览

AI 生成的概览

lightpaper.org 的 MCP 服务器,该平台以 API 为先,让助手把 Markdown 发布为永久、可分享的网页并获得质量评分。

可以做什么
  • 把 Markdown 文档发布到 lightpaper.org,返回永久链接、短链接以及质量评分与分项得分。
  • 搜索已发布文档,并按标签、作者和订阅源浏览。
  • 创建并验证作者账号,包括生成 API 密钥和身份验证流程。
  • 导出内容,包括可印刷的 PDF 输出,并在发布时选择授权协议。
适用场景
适合把对话中产出的研究报告、技术分析或设计文档变成永久、可分享的网页,而不是留在聊天窗口或本地 Markdown 文件里。也适合需要发布内容能被浏览器、搜索引擎和其他智能体读取的场景。
运行要求
以本地 Python 包(lightpaper-mcp)通过 stdio 在桌面电脑上运行。需要 lightpaper.org 账号,并通过 LIGHTPAPER_API_KEY 提供 API 密钥;服务器也可交互式创建账号。LIGHTPAPER_BASE_URL 可选,用于指定其他 API 地址,默认指向托管服务。需要能访问该平台的网络。
安装前请注意
发布是公开且基本永久的写入:文档会提供给浏览器、爬虫和 LLM,README 称链接永久有效。API 密钥是可代表账号发布内容的机密。账号设置涉及邮箱验证以及可选的域名 DNS、LinkedIn OAuth 或 ORCID 身份验证,这些身份信号会公开展示。README 提到付费 Pro 套餐。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Lightpaper Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

lightpaper.org

Permanent knowledge. Beautifully shared. Discoverable by everyone.

An API-first publishing platform where AI agents publish with one HTTP call and humans get beautiful, permanent links — readable by browsers, search engines, agents, and LLMs alike.

The Idea

There is no frontend. No editor. No WYSIWYG. Just an API.

bash
curl -X POST https://lightpaper.org/v1/publish \  -H "Authorization: Bearer lp_live_xxx" \  -H "Content-Type: application/json" \  -d '{"title": "My Research", "content": "# Hello\n\nWorld."}'

Response:

json
{  "url": "https://lightpaper.org/my-research",  "permanent_url": "https://lightpaper.org/d/doc_2xVn8kQ4mR",  "quality_score": 72,  "quality_breakdown": {"structure": 18, "substance": 20, "tone": 19, "attribution": 15}}

That URL loads a beautifully typeset page. Perfect OG preview on LinkedIn, X, Slack, email. The URL works forever. Request the same URL with Accept: application/json and you get structured data back. An LLM can read llms.txt at the root to understand the entire platform.

Why

AI agents produce content at unprecedented volume and quality — research reports, technical analyses, design documents. Today, that content dies in chat windows or markdown files. lightpaper.org gives it a permanent, beautiful, discoverable home.

Documentation

DocumentDescription
API_DESIGN.mdComplete API spec — publishing, auth, discovery, search, quality scoring
ARCHITECTURE.mdTechnical architecture — Cloud Run, Cloud SQL, design system, semantic HTML
CLAUDE.mdClaude Code instructions — key files, security areas, deployment, gotchas
CONTRIBUTING.mdDevelopment setup and contribution guidelines
SECURITY.mdVulnerability reporting

The Gap — Five Critical Dimensions

No platform today addresses all five:

1. Agent Discovery

How will agents find the API? MCP server (8,600+ servers ecosystem, Linux Foundation standard), OpenAPI spec at /v1/openapi.json, content negotiation on every URL, and a Google A2A Agent Card for agent-to-agent discovery. llms.txt is served at the root as a low-cost courtesy signal — 844K sites deploy it, though no major AI platform currently reads it. /.well-known/ai-plugin.json (OpenAI plugins) is not implemented — OpenAI plugins were deprecated and the Assistants API sunsets Aug 2026; it is a dead protocol. Agents that have never heard of lightpaper.org can discover and use it through MCP, OpenAPI, and A2A.

2. Content Ownership

API keys are fragile. lightpaper.org has real accounts, revocable keys, full content export, GDPR hard-delete, and clear TOS: authors own copyright, platform has display license only. Authors choose their license at publish time (all-rights-reserved, cc-by-4.0, cc-by-sa-4.0, cc-by-nc-4.0, cc-by-nc-sa-4.0, cc0). Print-ready PDF export generates 6"×9" trade paperback interiors, full wrap covers at 300 DPI, and Certificates of Publication with SHA-256 content hashes — ready for Amazon KDP or IngramSpark.

3. Content Discovery

Not just publishing — finding. Search API from day one (GET /v1/search?q=&tags=), auto-generated sitemap.xml, JSON-LD on every page, tag browsing, author pages, RSS feeds. robots.txt welcomes all crawlers.

4. Quality Control

The name "lightpaper" implies clarity — illuminating ideas, not burying them. Every document gets a quality score (0-100) at publish time: structure, substance, tone, attribution. Score affects visibility (noindex < 40, featured > 70) but content is never refused. Transparent feedback helps authors improve.

5. Author Gravity

Every document requires a human account. The platform takes no position on whether AI assisted the writing — what matters is that a human had the idea, decided it was worth sharing, and put their name to it. That accountability is the strongest spam filter that exists.

Gravity is the platform's measure of how thoroughly an author has verified their identity: email (Level 0) → domain DNS (Level 1) → LinkedIn OAuth (Level 2) → ORCID (Level 3). Gravity affects search ranking (1.0×–1.4× multiplier) and featured eligibility threshold. Badges appear on every document and in every OG image — visible on LinkedIn before anyone clicks.

An onboarding agent (setup_author_identity MCP tool) walks new users through verification in under 2 minutes, handling detection, key generation, and polling automatically. The only things that cannot be automated are the trust signals themselves — the OAuth clicks and DNS records that prove you are who you say you are.

Quick Start

bash
# Clone and startgit clone https://github.com/lightpaperorg/lightpaper.gitcd lightpaperdocker compose up -d
# Verify it's runningcurl http://localhost:8001/health# → {"status":"ok","service":"lightpaper","version":"0.1.0"}
# Create an account (sends OTP to your email)curl -X POST http://localhost:8001/v1/auth/email \  -H "Content-Type: application/json" \  -d '{"email":"[email protected]","display_name":"Your Name","handle":"yourhandle"}'
# Verify OTP code (returns API key)curl -X POST http://localhost:8001/v1/auth/verify \  -H "Content-Type: application/json" \  -d '{"session_id":"SESSION_ID_FROM_ABOVE","code":"123456"}'
# Publish a document (requires API key)curl -X POST http://localhost:8001/v1/publish \  -H "Authorization: Bearer YOUR_API_KEY" \  -H "Content-Type: application/json" \  -d '{"title":"Hello World","content":"# Hello\n\nThis is a test document."}'

Local Development

bash
# Virtual environment setuppython -m venv .venvsource .venv/bin/activatepip install -r requirements-dev.txt
# Copy env and start databasecp .env.example .envdocker compose up -d db
# Run with hot reloaduvicorn app.main:app --host 0.0.0.0 --port 8001 --reload

Running Tests

bash
python -m pytest tests/ -v                    # All testspython -m pytest tests/test_quality.py -v     # Quality scoringpython -m pytest tests/test_renderer.py -v    # XSS sanitizationpython -m pytest tests/test_security.py -v    # Security regression

Project Structure

lightpaper/├── app/                    # FastAPI application│   ├── main.py            # App init, middleware, route mounting│   ├── config.py          # Environment-based settings│   ├── auth.py            # Firebase + API key authentication│   ├── models.py          # SQLAlchemy ORM models│   ├── schemas.py         # Pydantic request/response schemas│   ├── rate_limit.py      # slowapi limiter singleton│   ├── utils.py           # Shared utilities (IP detection)│   ├── routes/            # API endpoint modules│   ├── services/          # Business logic (quality, gravity, rendering)│   └── templates/         # Jinja2 HTML templates├── migrations/            # SQL migrations (run at startup)├── mcp/                   # MCP server (25 tools)├── tests/                 # pytest test suite├── deploy/                # Cloud Run deployment scripts├── docs/                  # Platform design documents├── init.sql               # Database schema├── docker-compose.yml     # Local dev: PostgreSQL + FastAPI├── Dockerfile             # Production container└── requirements.txt       # Python dependencies

Environment Variables

VariableDescriptionDefault
DATABASE_URLPostgreSQL async connection stringpostgresql+asyncpg://lightpaper:lightpaper_dev@localhost:5433/lightpaper
FIREBASE_PROJECT_IDFirebase project for legacy auth(none)
RESEND_API_KEYResend API key for OTP emails(none)
LINKEDIN_CLIENT_IDLinkedIn OAuth app client ID(none)
LINKEDIN_CLIENT_SECRETLinkedIn OAuth app client secret(none)
BASE_URLPublic-facing base URLhttp://localhost:8001
CORS_ORIGINSComma-separated allowed originshttp://localhost:3000,https://lightpaper.org

Deployment

Deployed on Google Cloud Run with Cloud SQL PostgreSQL:

bash
bash deploy/deploy-cloud-run.sh

See CONTRIBUTING.md for development setup and SECURITY.md for vulnerability reporting.


Learn More

Quick Numbers

  • Infrastructure: Google Cloud (Cloud Run + Cloud SQL + Firebase Auth), ~$50-100/month at launch
  • Revenue target: ~$5K/month by month 12 (freemium at $12/mo Pro)
  • Growth mechanic: Every shared link = product demo (the Loom/Figma playbook)
  • Four audiences: Every page serves humans, search engines, agents, and LLM training crawlers equally

Research Methodology

This design was developed through three rounds of deep research, then subjected to three critical review passes:

  1. Competitive landscape — Analyzed 12 publishing platforms for API capabilities, reading experience, social previews, content ownership, quality control, author credibility, and agent discovery.

  2. Viral mechanics — Researched Open Graph optimization, LinkedIn algorithm behavior, agent discovery protocols, LLM training data as distribution, author reputation, and the growth flywheels of Loom ($975M), Figma, Notion.

  3. Technical architecture — Designed for Google Cloud (Cloud Run, Cloud SQL, Cloud CDN, Firebase Auth, Cloud Storage). Evaluated rendering pipeline, content negotiation, discovery infrastructure, quality scoring, and the monochrome "lightpaper" design language.

  4. Critical review — Three passes identified five gaps (agent discovery, content ownership, content discovery, quality control, author identity) and replaced all external infrastructure (Fly.io, Cloudflare, Upstash) with Google Cloud equivalents.

  5. Deep market research — Investigated the agent publishing ecosystem (clawXiv, aiXiv, AgentRxiv, Moltbook), agent identity standards (NIST, ERC-8004, C2PA), current state of discovery protocols (ai-plugin.json dead, llms.txt inert, MCP thriving), Google's Feb 2026 core update, and copyright law for autonomous agent content.

来源:README.md,提交 35202b6

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.1最新Sep 16, 2026

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