Annolux Search

⚡ Annolux

Curated English & Chinese Search API and MCP for AI Agents & RAG Systems

*Search that can show its work. Every result carries an explicit fetched_at timestamp and provenance.*

🌐 Website • 📖 API Docs • ⚡ MCP Quickstart • 📊 Frozen Benchmarks • 📁 Examples • 🇨🇳 中文文档

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💡 Why Annolux?

Current web search APIs for AI agents suffer from three fatal flaws:

1. Garbage in, garbage out: Commercial search engines index millions of SEO farms, scraped spam, and auto-generated noise that pollute LLM context windows.
2. Missing time-provenance: LLMs hallucinate current state because search APIs omit the exact snapshot timestamp (fetched_at).
3. Predatory billing: Paying full price for failed requests, empty outputs, or rate-limited retries.

Annolux solves this with an agent-first curated approach:

• 🛡️ Curated Bilingual Technical Index: High-signal English & Chinese corpus (Rust, Go, Python, AI/ML, Official Docs, RFCs, GitHub, arXiv).
• 🕒 Explicit `fetched_at` Timestamp: Every ranked hit reveals the exact second it was ingested—enabling grounded citations and temporal reasoning.
• 🎯 Predictable Ledger Billing: Exactly 1 credit per successful 2xx response. Errors, timeouts (504), rate limits (429), and bad requests cost 0 credits.
• 🧩 Native Model Context Protocol (MCP): Zero setup across Claude Code, Cursor, Windsurf, Cline, Zed, and Claude Desktop.
• 🚀 1,000 Free Credits Every Month: Sign in with GitHub or Google at annolux.com and start querying in 30 seconds.

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🥊 Comparison: Annolux vs. Generic Search APIs

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📦 Quick Installation

Node.js 18+ is the only prerequisite. Start in the zero-config sandbox—no account or API key is required:

npx -y annolux-mcp

For the full monthly allowance, create a free key at annolux.com and pass it through the process environment:

ANNOLUX_API_KEY=ann_live_YOUR_API_KEY npx -y annolux-mcp

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🔌 MCP Integration

Annolux implements the official Model Context Protocol (MCP) specification with a single, high-efficiency tool: search_web.

⚡ 1-Click Installation (Cursor & Smithery)

• Cursor: Click to install natively via deep link.
• Smithery CLI:

  npx -y @smithery/cli install annolux-mcp --client claude

npx -y @smithery/cli install annolux-mcp --client cursor

- **Glama Online Playground**: Test queries instantly without local setup on [Glama.ai](https://glama.ai/mcp/servers/eason4kim-rocket/annolux).

1. Claude Code

claude mcp add annolux -- npx -y annolux-mcp

This starts in sandbox mode. To use an account key, add it with -e ANNOLUX_API_KEY=ann_live_YOUR_API_KEY before --.

2. Cursor / Windsurf

Add to your project .cursor/mcp.json or global configuration:

{

"mcpServers": { "annolux": { "command": "npx", "args": ["-y", "annolux-mcp"], "env": { "ANNOLUX_API_KEY": "ann_live_YOUR_API_KEY" } } } }

3. Claude Desktop

Add to claude_desktop_config.json:

{

"mcpServers": { "annolux": { "command": "npx", "args": ["-y", "annolux-mcp"], "env": { "ANNOLUX_API_URL": "https://api.annolux.com", "ANNOLUX_API_KEY": "ann_live_YOUR_API_KEY" } } } }

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🚀 HTTP API Quickstart

Standard Search Endpoint

POST https://api.annolux.com/api/v1/search

Authorization: Bearer ann_live_YOUR_API_KEY Content-Type: application/json

{

"query": "tokio async runtime memory model", "domains": ["tokio.rs", "docs.rs", "github.com"], "deduplicate": true, "limit": 5, "timeout": 10, "ranking": "default" }

Python

import os

import requests

response = requests.post( "https://api.annolux.com/api/v1/search", headers={"Authorization": f"Bearer {os.environ.get('ANNOLUX_API_KEY')}"}, json={ "query": "DeepSeek R1 architecture reinforcement learning", "limit": 5, "deduplicate": True }, timeout=15 )

data = response.json() for result in data.get("results", []): print(f"[{result['fetched_at']}] {result['title']} -> {result['url']}")

TypeScript / Node.js

const res = await fetch("https://api.annolux.com/api/v1/search", {

method: "POST", headers: { "Authorization": Bearer ${process.env.ANNOLUX_API_KEY}, "Content-Type": "application/json" }, body: JSON.stringify({ query: "vLLM PagedAttention implementation details", limit: 5, deduplicate: true }) });

const data = await res.json(); console.log(Credits Remaining: ${res.headers.get("X-Annolux-Credits-Remaining")}); console.log(data.results);

cURL

curl -s -X POST https://api.annolux.com/api/v1/search \

-H "Authorization: Bearer ann_live_YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "Go sync.Pool benchmark best practices", "limit": 3 }' | jq .

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🏛️ Architecture & Mechanics

┌─────────────────────────────────────────────────────────────┐

│ AI Agent / RAG Application │ │ (Claude Code / Cursor / LangChain / Custom LLM) │ └──────────────────────────────┬──────────────────────────────┘ │ Stdio MCP / HTTPS REST Request │ ▼ ┌─────────────────────────────────────────────────────────────┐ │ Annolux Gateway API Engine │ │ ┌─────────────────────────┐ ┌───────────────────────┐ │ │ │ 1. Account & Rate Limit │ ──► │ Reserve 1 Credit │ │ │ │ (5 RPS, Burst 10) │ │ in /data/accounts.db │ │ │ └─────────────────────────┘ └───────────────────────┘ │ │ │ │ │ ▼ │ │ ┌───────────────────────────────────────────────────────┐ │ │ │ 2. Bilingual FTS Ranker (/data/index.db) │ │ │ │ • Curated English & Chinese Corpus │ │ │ │ • SimHash Content-Deduplication Engine │ │ │ │ • Domain Filter & Exact Substring Match │ │ │ └───────────────────────────────────────────────────────┘ │ │ │ │ │ ▼ │ │ ┌───────────────────────────────────────────────────────┐ │ │ │ 3. Atomic Response & Ledger Settlement │ │ │ │ • 2xx Success ──► Commit 1 Credit & Attach Timing │ │ │ │ • 4xx/5xx Err ──► Release Reservation (0 Cost) │ │ │ └───────────────────────────────────────────────────────┘ │ └──────────────────────────────┬──────────────────────────────┘ │ JSON with exact fetched_at & verified URL │ ▼ [ Grounded LLM Response ]

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📊 Search Quality & Frozen Benchmarks

Annolux evaluates search retrieval performance against an immutable, frozen blind set of 40 complex bilingual queries. The ranking weights are never tuned on the test set.

*All benchmarks are evaluated client-side under full concurrency load.*

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💳 Transparent Pricing

• No overage charges.
• Errors, rate-limits, and timeouts are 100% free (0 credit charged).
• Up to 3 active API keys per account.

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📁 Examples & Recipes

Check the examples/ directory for production-ready starters:

• 01-claude-code-literature-research: Automated technical survey agent with timestamped citations.
• 02-cursor-authority-domain-refactor: Restrict search to official doc domains (react.dev, go.dev) for zero-hallucination refactoring.
• 03-production-rag-temporal-pipeline: Production RAG hybrid search pipeline with fallback retrieval.
• 04-n8n-ai-research-agent: Ready-to-import n8n AI Agent workflow with community node (n8n-nodes-annolux) and temporal citations.

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🤝 Community & Support

• File bug reports or feature requests on GitHub Issues.
• Review SECURITY.md for private vulnerability reporting.
• Public OpenAPI specification: [annolux.com/openapi.json](https://annolux.