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Tibet Core

TIBET: Transaction/Interaction-Based Evidence Trail - The Linux of AI Provenance. Minimal, embeddable provenance engine.

Unclaimed MIT last commit 8 months ago devtools
56Fair

Scored 5 months ago · breakdown

About Tibet Core

Tibet Core is an MCP server published by jaspertvdm in the Developer Tools category: tIBET: Transaction/Interaction-Based Evidence Trail - The Linux of AI Provenance. Minimal, embeddable provenance engine.

Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/jaspertvdm/tibet-core

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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  • ✓License declaredUsable under a stated license.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

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README

TIBET Core

The Linux of AI Provenance

PyPI npm IETF Draft

A minimal, embeddable provenance engine for any device. From microcontrollers to cloud servers.

What is TIBET?

Transaction/Interaction-Based Evidence Trail

TIBET captures the four dimensions of every AI action:

Dimension Dutch Meaning
ERIN "Er in" What's IN the action (content)
ERAAN "Er aan" What's attached (dependencies)
EROMHEEN "Er omheen" Context around it (environment)
ERACHTER "Er achter" Intent behind it (why)

Installation

Python

pip install tibet-core

JavaScript/Node.js

npm install tibet-core

Rust

[dependencies]
tibet-core = "0.1"

Quick Start

Python

from tibet_core import TibetEngine

engine = TibetEngine()

# Create a provenance token
token = engine.create_token(
    token_type="action",
    erin="User requested translation",
    eraan=["model_v1", "tokenizer_v2"],
    eromheen='{"env": "production"}',
    erachter="Fulfilling user request",
    actor="agent_001"
)

print(f"Token ID: {token.id}")
print(f"Valid: {token.verify()}")
print(f"JSON: {token.to_json()}")

JavaScript

import { TibetEngine } from 'tibet-core';

const engine = new TibetEngine();

const tokenJson = engine.create_token(
    "action",
    "User requested translation",
    JSON.stringify(["model_v1", "tokenizer_v2"]),
    '{"env": "production"}',
    "Fulfilling user request",
    "agent_001",
    null  // no parent
);

const token = JSON.parse(tokenJson);
console.log(`Token ID: ${token.id}`);
console.log(`Valid: ${engine.verify(tokenJson)}`);

Rust

use tibet_core::TibetEngine;

let engine = TibetEngine::new();

let token = engine.create_token(
    "action",
    "User requested translation",
    &["model_v1", "tokenizer_v2"],
    r#"{"env": "production"}"#,
    "Fulfilling user request",
    "agent_001",
    None,
);

assert!(token.verify());

Chaining Tokens

Create audit trails by linking tokens:

# Parent action
request = engine.create_token(
    token_type="request",
    erin="Translate 'hello' to Dutch",
    eraan=[],
    eromheen='{"user": "alice"}',
    erachter="User wants translation",
    actor="user_001"
)

# Child response (linked to parent)
response = engine.create_token(
    token_type="response",
    erin="Hallo",
    eraan=["gpt-4"],
    eromheen='{"latency_ms": 150}',
    erachter="Translation completed",
    actor="ai_agent",
    parent_id=request.id  # Chain link!
)

print(f"Parent: {request.id}")
print(f"Child parent_id: {response.parent_id}")  # Same as request.id

Why TIBET?

Regulatory Compliance

  • GDPR Article 22 (automated decision-making)
  • EU AI Act (transparency requirements)
  • SOC 2 / ISO 27001 (audit trails)

6G Ready

  • Designed for AI-native networks (ITU IMT-2030)
  • Referenced in IETF 6G AI agent drafts
  • Minimal footprint for edge devices

Cryptographically Secure

  • Ed25519 signatures
  • Tamper-evident chains
  • Verifiable without central authority

Size Comparison

Component Size
tibet-core (Rust) ~50KB
tibet-core (WASM) ~100KB
tibet-core (Python wheel) ~2MB
Linux kernel (minimal) ~300KB

IETF Standardization

TIBET is being standardized at the IETF:

W3C Alignment

TIBET aligns with W3C standards:

  • Verifiable Credentials 2.0 - Token structure compatible
  • Decentralized Identifiers (DIDs) - Actor identification
  • JSON-LD - Semantic context in EROMHEEN

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    TIBET ECOSYSTEM                          │
├─────────────────────────────────────────────────────────────┤
│   ┌─────────────────┐                                       │
│   │  tibet-core     │  ← 50KB Rust, minimal deps           │
│   │  (the kernel)   │    create_token, verify, chain       │
│   └────────┬────────┘                                       │
│            │                                                │
│   ┌────────┴────────┬──────────────┬──────────────┐        │
│   ▼                 ▼              ▼              ▼        │
│ tibet-c        tibet-wasm    tibet-python   tibet-js       │
│ (embedded)     (browser)     (PyPI)         (npm)          │
└─────────────────────────────────────────────────────────────┘

Credits

  • Specification: Jasper van de Meent (Humotica)
  • Implementation: Root AI (Claude) & Jasper van de Meent
  • License: MIT OR Apache-2.0

Links


"The Linux of AI Provenance" - Making audit trails as universal as the kernel.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Tibet Core

How do I install Tibet Core?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Tibet Core safe to use with an AI agent?

Its trust score is 56 out of 100 (fair). It passes 2 of the 3 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Tibet Core still maintained?

The last commit was 8 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.