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Give CLI coding agents persistent memory, dependency awareness, and architecture constraint validation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "project-brain-mcp" yet — see the docs or source repo.
Based on the current codebase dependency graph, check whether this refactoring plan violates architectural constraints and identify high-risk impact points: move user authentication logic from auth-service into api-gateway.
A review of architectural conflicts, affected modules, potential risks, and safer refactoring suggestions.
Store this engineering decision and keep referencing it in future tasks: use Zustand for frontend state management instead of adding Redux; all new modules must access the database through the service layer.
Persistent decision memory that can be reused and automatically referenced in later coding or planning tasks.
Based on the current project structure and existing conventions, automatically generate a constraints.md file covering architecture boundaries, dependency rules, naming conventions, and forbidden patterns.
A draft constraints.md file ready to add to the repository for consistent team and agent execution.
Give AI coding assistants local long-term memory with searchable lessons and patterns.
Give language models persistent memory for onboarding, rule recall, and consistent coding.
Give AI coding agents structured access to project architecture and decisions.
Manage project tasks, milestones, decisions, and team messaging via MCP.
Build local codebase memory for AI agents with search and architecture inspection.
Give AI coding assistants persistent, conflict-aware memory across projects and sessions.