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.

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

Tool	Description	Read-only
query_knowledge	Search across all knowledge units with filters	Yes
batch_query	Search multiple topics in one call (max 10)	Yes
get_unit	Retrieve full markdown content by ID	Yes
list_domains	List all domains with unit counts	Yes
suggest_question	Submit a topic request for new unit creation	No
report_issue	Flag incorrect, outdated, or broken content	No

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

Type	Count	Description
product_comparison	418	Best-of roundups with decision logic and buy links
concept	336	Definitions of terms agents often get wrong
software_reference	239	Code examples, anti-patterns, decision trees
execution_recipe	202	Step-by-step implementation plans
erp_integration	166	API capabilities, rate limits, data mapping
agent_prompt	55	System prompts for pipeline sub-agents
assessment	54	Structured scoring frameworks
decision_framework	35	Decision trees with trade-offs
benchmark	28	Industry benchmarks by segment
rule	28	Actionable directives with evidence

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