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Give AI coding assistants persistent memory for preferences, build steps, and architecture decisions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "evermemos-mcp-server" yet — see the docs or source repo.
Please remember these long-term project conventions: use TypeScript for the backend, always run npm test and eslint before commits, and keep API responses in the format { code, message, data }. Follow these rules by default in future sessions.The tool stores project preferences and workflow rules so the AI can reuse them automatically in later sessions.
Remember this project's build and release process: run pnpm install first, then pnpm build, the Docker image name is acme-web, and production is deployed to AWS ECS via GitHub Actions. Use this process whenever I ask about deployment later.
The tool records the standard build and deployment workflow for quick reuse in future assistance.
Please remember this architecture decision: keep user and order services in a modular monolith for now instead of splitting into microservices; use Redis for caching; handle async jobs with BullMQ. Base future system design advice on these assumptions.
The tool preserves key architecture decisions and context so future AI guidance stays consistent.
Give AI coding assistants long-term memory across sessions for persistent context.
Give AI coding tools persistent memory across sessions, devices, and workflows.
Give coding agents persistent cross-session memory for project context and decisions.
Give AI agents persistent memory and semantic retrieval across conversations.
Persist Claude Code conversations and retrieve relevant context across sessions.
Provide shared cross-session memory storage, retrieval, and governance for MCP AI tools.