Development Guide
Guidance for developers and implementers working with MSP-1 in practical environments, including structural considerations, workflow patterns, and implementation-oriented reference material.
MSP-1 - AI-friendly semantics for trusted information.
Labs is the open development and experimentation space within the MSP-1 ecosystem. It is where implementation thinking, proposed extensions, evaluative methods, prototype tooling, and forward-looking concepts can be explored without expanding the core protocol itself.
This section is intended for developers, researchers, implementers, and technically curious observers who want to explore how MSP-1 can be extended, tested, evaluated, and applied in practical workflows. Labs is deliberately open in posture: an invitation to build, examine, and contribute ideas around the protocol.
Guidance for developers and implementers working with MSP-1 in practical environments, including structural considerations, workflow patterns, and implementation-oriented reference material.
Proposed and developing MSP-1 extensions that expand possible use cases while preserving the protocol’s minimal core and graceful degradation principles.
Tools, methods, and structured approaches for assessing MSP-1 outputs, interpretive effects, and implementation quality across different models and workflows.
Experimental work designed to test how MSP-1 affects inference, interpretation, consistency, and downstream reasoning across real and simulated AI workflows.
Early-stage ideas, theoretical directions, and adjacent explorations that may inform future tooling, implementation patterns, or ecosystem growth.
A future-facing area for software development resources, implementation helpers, and practical tooling support for teams building with MSP-1-aware systems.
The public development home for MSP-1 repositories, schemas, supporting resources, and open-source implementation materials across the ecosystem.