letta vs piia-engram
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.; piia-engram: piia-engram is a local-first AI identity layer that stores your profile, preferences, lessons learned, and key decisions as local JSON files. It exposes them through the MCP protocol so that all compatible AI tools (like Claude Code, Codex, and Cursor) read the same identity, eliminating the need to re-explain yourself across sessions, tool switches, or updates.
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.
Maintain consistent identity when switching between multiple AI coding tools
Side-by-Side Comparison
lettapiia-engramFeatures
lettapiia-engramUse Cases
lettapiia-engramBest For
lettapiia-engramFAQ
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