knowledgelib.io

AI Knowledge Library — structured, cited knowledge units for AI agents. Pre-verified answers that save tokens, reduce hallucinations, and cite every source.

What is this?

1,800+ knowledge units across 18 domains (consumer electronics, software, business strategy, ERP integration, compliance, energy, finance, and more). Each unit answers one canonical question with:

• Confidence scores (0.0-1.0) per published methodology

• Inline source citations from 5-8 authoritative sources

• Freshness tracking with verified dates and temporal validity

• Quality status — verified, needs_review, or unreliable

• Knowledge graph — related units with typed edges

One API call replaces 5 web searches and 8,000 tokens of parsing.

Related MCP server: Swiss Truth MCP

Quick Start

MCP Server (Claude, Cursor, Windsurf)

npx knowledgelib-mcp

Or add to claude_desktop_config.json:

{
  "mcpServers": {
    "knowledgelib": {
      "command": "npx",
      "args": ["knowledgelib-mcp"]
    }
  }
}

MCP over HTTP (no install needed)

POST https://knowledgelib.io/mcp

Streamable HTTP transport, JSON-RPC 2.0, MCP spec 2025-03-26.

REST API

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

# Batch search (up to 10 queries)
curl -X POST https://knowledgelib.io/api/v1/batch \
  -H "Content-Type: application/json" \
  -d '{"queries":[{"q":"earbuds"},{"q":"headphones"}]}'

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

# Health check
curl https://knowledgelib.io/api/v1/health

LangChain (Python)

pip install langchain-knowledgelib

from langchain_knowledgelib import KnowledgelibRetriever
retriever = KnowledgelibRetriever()
docs = retriever.invoke("best wireless earbuds")

n8n

npm install n8n-nodes-knowledgelib

MCP Tools

All read-only tools are marked with readOnlyHint: true and idempotentHint: true per MCP spec 2025-03-26, enabling parallel execution by agents.

API Features

• Structured error codes with retryable flag and retry_after_ms

• ETag / If-None-Match caching (304 Not Modified)

• Correlation IDs (X-Request-Id header on all responses)

• Quality status (verified / needs_review / unreliable) on all results

• Related units for knowledge graph traversal

• Content previews (150-char summaries without fetching full unit)

• Token budgeting (total_tokens across results)

• Rate limiting on write endpoints (10 suggestions/hr, 20 feedback/hr)

• Zod validation with per-field error messages

Entity Types

Discovery

• /llms.txt — Plain-text guide for LLMs

• /llms-full.txt — Complete index of all questions

• /.well-known/ai-knowledge.json — Machine-readable manifest

• /catalog.json — Full catalog with metadata

• /for-agents — Integration guide

Links

• Website: https://knowledgelib.io

• npm: https://www.npmjs.com/package/knowledgelib-mcp

• PyPI: https://pypi.org/project/langchain-knowledgelib/

• HTTP MCP: https://knowledgelib.io/mcp

• OpenAPI: https://knowledgelib.io/api/v1/openapi.json

• GPT Actions: https://knowledgelib.io/.well-known/openapi-gpt.json

License

CC BY-SA 4.0