🧬 KIP (Knowledge Interaction Protocol)

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A graph-oriented interaction protocol designed specifically for Large Language Models,
bridging the gap between LLM and Knowledge Graph.

What is KIP?

KIP (Knowledge Interaction Protocol) is a standard interaction protocol that bridges the gap between LLM (Probabilistic Reasoning Engine) and Knowledge Graph (Deterministic Knowledge Base). It is not merely a database interface, but a set of memory and cognitive operation primitives designed specifically for intelligent agents.

Large Language Models (LLMs) have demonstrated remarkable capabilities in general reasoning and generation. However, their "Stateless" essence results in a lack of long-term memory, while their probability-based generation mechanism often leads to uncontrollable "hallucinations" and knowledge obsolescence.

KIP was born to solve this problem through Neuro-Symbolic AI approach.

Key Benefits

• 🧠 Memory Persistence: Transform conversations, observations, and reasoning results into structured "Knowledge Capsules"
• 📈 Knowledge Evolution: Complete CRUD and metadata management for autonomous learning and error correction
• 🔍 Explainable Interaction: Make every answer traceable and every decision logically transparent
• ⚡ LLM-Optimized: Protocol syntax optimized for Transformer architectures with native JSON structures

Quick Start

// Query: Find all drugs that treat headache
FIND(?drug.name)
WHERE {
  ?drug {type: "Drug"}
  (?drug, "treats", {name: "Headache"})
}
LIMIT 10

// Store: Create a new knowledge capsule
UPSERT {
  CONCEPT ?aspirin {
    {type: "Drug", name: "Aspirin"}
    SET ATTRIBUTES { molecular_formula: "C9H8O4", risk_level: 2 }
    SET PROPOSITIONS { ("treats", {type: "Symptom", name: "Headache"}) }
  }
}
WITH METADATA { source: "FDA", confidence: 0.95 }

// Explore: Discover schema
DESCRIBE PRIMER

Documentation

Core Concepts

Cognitive Nexus

A knowledge graph composed of Concept Nodes and Proposition Links, serving as the AI Agent's unified memory brain.

graph LR
    subgraph "Cognitive Nexus"
        A[Drug: Aspirin] -->|treats| B[Symptom: Headache]
        A -->|is_class_of| C[DrugClass: NSAID]
        A -->|has_side_effect| D[Symptom: Stomach Upset]
    end

KIP Instruction Sets

Schema Bootstrapping

KIP uses a self-describing schema where type definitions are stored within the graph itself:

• $ConceptType: Meta-type for defining concept node types
• $PropositionType: Meta-type for defining proposition predicates
• Domain: Organizational units for knowledge

Resources

This repository includes ready-to-use resources for building KIP-powered AI agents:

📦 Knowledge Capsules (capsules/)

Pre-built knowledge capsules for bootstrapping your Cognitive Nexus:

🔌 MCP Server (mcp/)

kip-mcp-server - Model Context Protocol server that exposes KIP tools over stdio:

• Tools: execute_kip, list_logs
• Resources: kip://docs/SelfInstructions.md, kip://docs/KIPSyntax.md
• Prompt: kip_bootstrap for ready-to-inject system prompt

🎯 Agent Skills (skill/)

kip-cognitive-nexus - Publishable skill for AI agents:

• Python client script for anda_cognitive_nexus_server
• Complete syntax reference and agent workflow guide

Implementations

Version History

Full version history →

About Us

ICPanda is a community-driven project that aims to build the foundational infrastructure and applications that empower AI agents to thrive as first-class citizens in the Web3 ecosystem.

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License

Copyright © 2025 LDC Labs.

Licensed under the MIT License. See LICENSE for details.