<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> The Lucid AI SDK by Raijin Labs provides a TypeScript client library and an MCP server for interacting with the LucidLayer API. It enables developers to manage AI model and compute resources, orchestrate AI agents, and securely track AI inference through cryptographic proofs and receipts. The SDK targets developers building decentralized AI applications, AI marketplaces, and AI-powered tools, offering a structured way to integrate with the LucidLayer ecosystem.

How It Works

<2-4 sentences on core approach / design (key algorithms, models, data flow, or architectural choices) and why this approach is advantageous or novel.> The project consists of two main components: a TypeScript SDK client and an MCP (Model Context Protocol) server. The SDK offers a typed interface to the LucidLayer API, abstracting complex operations like creating and managing "passports" for AI models and compute resources, matching compute providers to model requirements based on defined policies, and generating/verifying "receipts" for AI inferences. The MCP server acts as a bridge, exposing these API functionalities as tools for AI assistants, facilitating agent orchestration and contribution proof generation via an Agent MMR (Merkle Message Root) system.

Quick Start & Requirements

• Primary install / run command (pip, Docker, binary, etc.).
  • SDK: npm install raijin-labs-lucid-ai
  • MCP Server: npx raijinlabs-mcp start
• Non-default prerequisites and dependencies (GPU, CUDA >= 12, Python 3.12, large dataset, API keys, OS, hardware, etc.).
  • Node.js and npm are required. Specific AI model runtimes (e.g., vLLM) and hardware (e.g., GPUs) may be necessary for certain operations, as detailed in model passport requirements.
• Estimated setup time or resource footprint.
  • Not specified.
• If they are present, include links to official quick-start, docs, demo, or other relevant pages.
  • SDK API Reference: typescript/README.md
  • SDK Examples: typescript/examples/
  • MCP Setup: mcp/README.md

Highlighted Details

• AI Agent Orchestration: Supports initializing agents, processing contribution vectors across epochs, and generating cryptographic proofs of contribution.
• Decentralized Compute Matching: Enables defining policies (regions, latency, cost, privacy) to match compute resources with model requirements.
• Verifiable Inference Receipts: Allows creation and cryptographic verification of receipts for AI inferences, ensuring data integrity and accountability.
• MCP Server for AI Assistants: Integrates LucidLayer API tools into AI assistants like Claude, Cursor, and VS Code.

Maintenance & Community

• Notable contributors, sponsorships, partnerships, deprecations, migrations, or other health signals if notable.
  • The project is maintained by Raijin Labs. Specific community links (Discord, Slack) or detailed contributor information are not explicitly provided in the README excerpt.
• Links to Discord/Slack, social handles, roadmap, etc.
  • Not specified.

Licensing & Compatibility

• License type and notable restrictions (GPL -> copyleft, SSPL, etc.).
  • MIT License.
• Compatibility notes for commercial use or closed-source linking.
  • The MIT license generally permits commercial use and integration with closed-source projects.

Limitations & Caveats

<1-3 sentences on caveats: unsupported platforms, missing features, alpha status, known bugs, breaking changes, bus factor, deprecation, etc. Avoid vague non-statements and judgments.> The provided README excerpt focuses on features and usage, offering no explicit details on known limitations, alpha/beta status, or potential adoption blockers beyond standard development prerequisites. The version numbers (SDK 0.4.1, MCP 0.2.2) suggest the project may still be in early development stages.