letta vs mcp-memory-keeper
letta: Letta is a powerful platform for building stateful AI agents equipped with advanced memory, enabling them to learn and self-improve over time. It provides both a command-line interface for local agent execution and a comprehensive API with Python and TypeScript SDKs for seamless integration into applications.; mcp-memory-keeper: MCP Memory Keeper is an MCP server that provides persistent context management for Claude AI coding assistants, preventing context loss during compaction. It offers features like session management, context saving/retrieval, checkpoints, search, and git integration. The server works across macOS, Linux, and Windows and can be installed via npx.
TL;DR
- You want a long-lived agent that remembers past work and rewrites its own memory and context over time.
- You want one agent reachable from CLI, desktop, browser, mobile and messaging apps, with subagents, schedules and hooks.
- You want memory you can inspect: the README says context is tracked in git and can sync to your own repository.
- You only need to add memory to an agent you already use through MCP; a small MCP memory server is a lighter fit.
- You rely on older Letta tutorials or the V1 API server: the project restructured, and the V1 server is retired.
- You want everything to work without signing in: Letta Cloud is the default backend and some features need it.
Long coding sessions with Claude Code
Side-by-Side Comparison
lettamcp-memory-keeperFeatures
lettamcp-memory-keeperUse Cases
lettamcp-memory-keeperBest For
lettamcp-memory-keeperFAQ
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