memories-sdk
memories-sdk
Use the SDK packages when an application needs memories.sh programmatically. Prefer @memories.sh/core for direct typed API access and @memories.sh/ai-sdk only when the caller already uses the Vercel AI SDK.
Workflow
More from webrenew/memories
memories-mcp
MCP server integration for memories.sh — the persistent memory layer for AI agents. Use when: (1) Configuring the memories.sh MCP server for any client (Claude Code, Cursor, Windsurf, VS Code, v0, Claude Desktop, OpenCode, Factory), (2) Using MCP tools to store, search, retrieve memories, run lifecycle session workflows, or manage reminders, (3) Understanding get_context vs search_memories vs list_memories, (4) Working with streaming memory tools for SSE content, (5) Troubleshooting MCP connection issues, (6) Choosing between cloud MCP (HTTP) and local MCP (stdio) transports.
33memories-dev
Developer guide for contributing to and extending the memories.sh codebase. Use when: (1) Understanding the memories.sh architecture and lifecycle model, (2) Adding new CLI commands or MCP tools, (3) Modifying the memory storage layer (SQLite/libSQL), (4) Working on the web dashboard (Next.js/Supabase), (5) Adding new generation targets for AI tools, (6) Extending cloud sync, session compaction, or embeddings functionality, (7) Debugging build, test, or deployment issues in the monorepo.
30memories-cli
CLI reference and workflows for memories.sh — the persistent memory layer for AI agents. Use when: (1) Running memories CLI commands to add, search, edit, or manage memories, (2) Managing lifecycle workflows (session/checkpoint/compaction/consolidation/OpenClaw memory files), (3) Setting up memories.sh in a new project (memories init), (4) Generating AI tool config files (CLAUDE.md, .cursor/rules, etc.), (5) Importing existing rules from AI tools (memories ingest), (6) Managing cloud sync, embeddings, git hooks, or reminders, (7) Troubleshooting with memories doctor, (8) Working with memory templates, links, history, tags, or reminder schedules.
29