VibeWise MCP
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- FlicenseNot gradedqualityAmaintenanceProvides a local-first, user-owned AI work identity layer that stores preferences, quality bars, lessons, decisions, and project context in inspectable JSON/Markdown files on your machine, so multiple MCP-compatible coding tools start from the same approved context. It enables reviewing, editing, overriding, and previewing exactly what any AI caller receives before anything is sent.-
- FlicenseNot gradedqualityAmaintenanceEnables users to give multiple MCP coding tools one local, user-owned AI work identity — preferences, quality bar, lessons, decisions, and project context kept as inspectable, editable files — so each agent starts from the same approved context with every write reviewable, reversible, or gated in strict mode. Provides cross-tool memory continuity across Claude Code, Codex, Cursor, Windsurf, and other MCP clients without requiring a cloud account.-
- FlicenseNot gradedqualityAmaintenanceEnables MCP-compatible coding agents to start from one portable, local-first identity and long-term knowledge layer, so preferences, quality bars, lessons, decisions, and project context carry across tools instead of being relearned per session. Everything the AI writes stays in local files the user can inspect, edit, approve, or override.-
- FlicenseNot gradedqualityAmaintenanceEnables MCP-compatible coding tools to start from one portable, local-first identity and knowledge layer containing the user's approved preferences, quality standards, lessons, decisions, and project context. It stores this in local files the user owns and can inspect, edit, or override, with governance over AI-proposed writes and no cloud account required.-
- AlicenseNot gradedqualityDmaintenanceAdds a human-in-the-loop checkpoint to MCP-capable AI coding agents, enabling them to pause and request user feedback before executing actions.8 npm72MIT
- FlicenseNot gradedqualityAmaintenanceEnables a local-first, user-owned AI work identity layer that lets multiple MCP coding tools share approved preferences, quality standards, lessons, decisions, and project context, with local files you can inspect, edit, and override.-
TDQS
Scored across 10 tools
Most tools map to distinct lifecycle stages (start, checkpoint, confirm, report, reset), but vibe_status and vibe_read_notes both surface gate/state info, and vibe_pause's 'resume' overlaps with vibe_start's 'resumes a paused/pending state'. Descriptions mostly disambiguate these, so confusion risk is low.
Every tool uses the same vibe_ prefix with a consistent snake_case noun/verb (vibe_status, vibe_start, vibe_checkpoint, vibe_map_update). No camelCase or mixed conventions, so the pattern is fully predictable.
10 tools is well within the ideal 3-15 range and each corresponds to a distinct step of the learning-gate workflow. No tool feels redundant or filler.
The surface covers the full learning lifecycle: activation, onboarding, checkpoints, confirmation, reporting, map maintenance, pause/resume, reset, and state reading. Minor gap: no explicit way to answer/close an onboarding session or query individual notes, but agents can work around these.