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DRIFT extension for MCP #10
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| # DRIFT | ||
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| **Decentralized Resource Identity & Trust Framework (DRIFT)** | ||
| Created by [Slava Tykhonov](https://github.com/4tykhonov) | ||
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| --- | ||
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| DRIFT is a decentralized identity and trust layer that propagates **traceable context** — such as sessions, prompts, user metadata, and spans — across AI tools and services in **event-driven environments** like the Model Context Protocol (MCP). | ||
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| ## 🧠 Background: Understanding Data Drift | ||
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| In software engineering, **data drift** is a key concern that can affect system reliability and trust in data processing pipelines. DRIFT helps mitigate these risks by making identity and changes traceable. | ||
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| Three common types of drift include: | ||
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| - **Infrastructure Drift** – Changes in the software environment that can break or invalidate infrastructure configurations. | ||
| - **Structural Drift** – Changes to the data schema that may invalidate databases or data contracts. | ||
| - **Semantic Drift** – Changes in the meaning of data without altering its structure, often caused by multiple developers independently modifying system components. | ||
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| By assigning decentralized identifiers (DIDs) and enforcing consistent, signed metadata, DRIFT supports systems in managing and auditing these types of drift. | ||
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| ## 🔍 What DRIFT Does | ||
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| DRIFT enables trusted interoperability between distributed AI components by providing unique, verifiable identities for all parts of an AI pipeline. | ||
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| ## ✨ Features | ||
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| - ✅ Assigns [DIDs (Decentralized Identifiers)](https://www.w3.org/TR/did-core/) to all entities: | ||
| - Sessions | ||
| - Prompts | ||
| - Users | ||
| - Tools | ||
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| - 🔐 Uses **public/private key cryptography** to: | ||
| - Sign events | ||
| - Verify authenticity of actions and actors | ||
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| - 🧱 Defines a **consistent metadata structure** for: | ||
| - Events | ||
| - Tools | ||
| - Services | ||
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| - 🔗 Supports **verifiable logs and data lineage**: | ||
| - Track where and how data was processed | ||
| - Ensure transparency in AI workflows | ||
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| ## 📦 Use Cases | ||
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| - Model Context Protocol (MCP) pipelines | ||
| - Distributed AI systems | ||
| - Event logging with trusted provenance | ||
| - Prompt and session tracking across tools | ||
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| --- | ||
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| ## 🛠️ Getting Started | ||
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| ```bash | ||
| # Clone the project | ||
| cd drift | ||
| python3 drift.py | ||
| ``` | ||
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I assume we should (some day)
git rmthis pyc file.