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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

peterbeck111/knowledgelib-io MCP server](https://glama.ai/mcp/servers/peterbeck111/knowledgelib-io/badges/score.svg)](https://glama.ai/mcp/servers/peterbeck111/knowledgelib-io) πŸ“‡ ☁️ - Search 1,500+ pre-verified, cited knowledge units across 16 domains.

README.md

knowledgelib.io

AI Knowledge Library β€” 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 β€” verified, needs_review, or unreliable
  • Knowledge graph β€” 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

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

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