Show HN: World Model MCP v0.10.0 – cross-runtime memory across 7 coding agents (github.com)

The release of World Model MCP v0.10.0 introduces significant advancements in cross-runtime memory management for AI coding agents, now expanding compatibility to seven platforms including OpenClaw, Hermes Agent, and Continue. This version enhances enforcement, provenance, and harness-neutral memory capabilities by implementing a temporal knowledge graph that validates code changes, tracks contradictions, and optimizes memory re-injection during compaction. With 27 tools and 22 CLI subcommands, this update also improves the ability to document and resolve coding mistakes more effectively, which is critical for improving programming efficiency and reducing errors. The significance of this update lies in its ability to provide a shared memory layer across diverse coding environments, enabling seamless integration and enhanced performance. Each new adapter has been thoroughly validated against their respective runtimes, ensuring reliable functionality and addressing potential issues such as path management. The update reinforces best practices in memory utilization by providing evidence-type decay and provenance systems that allow coding agents to learn from previous interactions. The expansion of the contradiction-resolution benchmark and the incorporation of multi-seed replication testing methodologies further solidify the project's commitment to robust, transparent AI development practices.