Hoofy vs letta
Hoofy: Hoofy is an MCP server that solves memory loss, hallucinated implementations, and unstructured AI workflows. It provides persistent context across sessions, spec-driven development pipelines, and adaptive change management for any MCP-compatible AI tool. Built in Go, it runs as a single binary with zero dependencies.; 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.
TL;DR
Start a new project: use the full project pipeline from vague idea to validated architecture
- 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.
Side-by-Side Comparison
HoofylettaFeatures
HoofylettaUse Cases
HoofylettaBest For
HoofylettaFAQ
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