knowledgelib.io — AI Knowledge Library

Structured, cited knowledge units built for AI agents. Pre-verified answers to high-friction questions with full source provenance, confidence scores, and freshness tracking. One knowledge unit replaces 5 web searches and 8,000 tokens of parsing.

Why

When AI agents need to answer complex questions, they run multiple web searches, fetch noisy pages, and spend thousands of tokens parsing and cross-referencing — often producing unreliable answers with no source trail. knowledgelib.io short-circuits this:

	Without knowledgelib.io	With knowledgelib.io
Token cost	3,000 - 8,000 tokens	~600 - 1,800 tokens
Sources cited	Usually none	100% — every claim linked to a source
Confidence	Unknown	Scored 0.0 - 1.0 per published methodology
Compute cost	$0.50 - $5.00 per question	$0.10 per query (API)
Freshness	Unknown	Verified date + update schedule on every unit

How It Works

Each knowledge unit is a self-contained answer to one canonical question. Units use YAML frontmatter for machine-readable metadata and inline source citations for auditability.

For AI agents (via web search — zero setup)

Every knowledge unit has its own web page optimized for search engine indexing. When your agent searches the web, our pages rank for AI-style queries (factual, specific, including year and data type). The page body IS the markdown — no HTML parsing needed.

For AI agents (via API / MCP)

# MCP Server (Claude, Cursor, any MCP client)
npx knowledgelib-mcp

# Direct API
curl https://knowledgelib.io/api/v1/query?q=best+wireless+earbuds+under+150

# Raw markdown unit
curl https://knowledgelib.io/api/v1/units/consumer-electronics/audio/wireless-earbuds-under-150/2026.md

See the full API documentation for endpoints, MCP setup, and pricing tiers.

Knowledge Unit Format

---
id: consumer-electronics/audio/wireless-earbuds-under-150/2026
canonical_question: "What are the best wireless earbuds under $150 in 2026?"
aliases:
  - "best budget earbuds 2026"
  - "wireless earbuds comparison under 150"
confidence: 0.88
last_verified: 2026-02-07
sources:
  - id: src1
    title: "Best Wireless Earbuds 2026"
    author: RTINGS.com
    url: https://www.rtings.com/headphones/reviews/best/...
    reliability: high
---

# Best Wireless Earbuds Under $150 (2026)

## Summary
[Structured answer with inline citations like [src1, src3]]

## Key Facts
- Specific numbers, thresholds, comparisons [src1]
- Every claim traced to a source [src2]

Available Knowledge Units

Best Wireless Earbuds Under $150 (2026)
Consumer Electronics > Audio | Confidence: 0.88 | Verified: 2026-02-07 | 8 sources | ~1,800 tokens
Comparison of 10 top models across 6 use cases. Specs, prices, codec support, ANC performance, and specific recommendations.
US Interconnection Queue Status (2025)
Energy > Grid Infrastructure | Confidence: 0.90 | Verified: 2025-04-15 | 3 sources | ~600 tokens
2,600 GW in queue, 4-5 year average wait, 14% completion rate. FERC Order 2023 impact analysis.

Discovery Channels

AI agents can find knowledgelib.io through multiple channels:

Channel	How	Setup
Web search	Pages rank for AI-style queries. Body is raw markdown.	Zero
MCP server	`npx knowledgelib-mcp`	One-time install
REST API	`GET /api/v1/query?q=...`	API key (free tier)
Catalog	`GET /catalog.json` — full index of all units	Zero
AI manifest	`GET /.well-known/ai-knowledge.json`	Zero

Trust & Verification

Every knowledge unit includes:

Confidence score (0.0 - 1.0) backed by published methodology
Source provenance — each claim cites specific sources with reliability ratings
last_verified date — when the unit was last checked against primary sources
Freshness indicator — how often the unit is updated (monthly / quarterly / yearly)
Version history — every change tracked with changelog