hjqcan/GoodMemory
by Various
Local-first, auditable memory layer for AI apps and coding agents — Codex, Claude Code, MCP, HTTP, TypeScript, and Python.
MCP
hjqcan/GoodMemory
Added 3 Sept 2026
Overview
GoodMemory is a local-first, auditable memory layer for AI applications and coding agents. It integrates with Codex, Claude Code, MCP, HTTP, TypeScript, and Python, allowing agents to store and retrieve memory while keeping data on local infrastructure.
Best for
Best for
Developers building AI agents that need persistent, auditable memory.
Use cases
- Give coding agents persistent memory across sessions
- Expose agent memory to tools via MCP or HTTP
- Audit memory reads and writes in AI workflows
How to use
Install
npx goodmemory -VClients listed in this record (not verified here)
Claude Desktop, Claude Code, Cursor, Windsurf, Cline, ChatGPT
Notes
17 stars on GitHub. Last updated 2026-08-22. Licensed MIT.
Pros
- Local-first design keeps data on your own infrastructure
- Auditable memory supports transparency and debugging
- Works with multiple agent ecosystems and protocols
Cons
- Very early-stage project with few stars and limited adoption
- No single vendor backing, so support is community-driven
- Requires self-hosting and setup for each environment
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
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