Alternatives

Products that do what projectmem does

Memory + judgment for AI coding agents (local, MIT)

1
Agentmemory▲322
Persistent memory for Claude Code, Codex & coding agents
May 2026 · agent-memory.dev
2
MemoryCustodian▲145
Repo-native memory for coding agents
Jul 2026 · github.com
3
Byterover▲505
Memory layer for your AI coding agents
2025
4RL
Recall – Local project memory for Claude Code▲138
Jun 2026 · github.com
5
Memori▲168
Persistent memory from agent trace, not just conversation
May 2026 · memorilabs.ai
6
ContextPool▲180
Persistent memory for AI coding agents
Apr 2026 · contextpool.io
7
Byterover 2.0▲239
Central Memory Layer For Dev Teams with Git-like System
2025
8
Kit For AI▲83
The memory layer for AI agents
Jul 2026 · kitforai.com
9
GitHub▲10
Local-first memory for your AI coding agent
Jun 2026 · github.com
10
PMB▲211
Stop re-explaining your project to AI coding agents
Jun 2026 · pmbai.dev
11
AskAIBase▲84
Memory infrastructure for AI coding agents
Feb 2026
12
Reference▲81
Local semantic search for AI agents
Aug 2026 · tryreference.com
13
DeltaMemory▲104
Fastest cognitive memory for AI Agents
Feb 2026
14
CogniMemo▲120
AI that remembers, learns, and evolves
Dec 2025
15
Actx0▲100
Memory infrastructure for AI agents.
17d ago · actx0.com
16PL
PMB – local memory for coding agents that shows if it is used▲26
Jun 2026 · pmbai.dev
17LA
Linggen – A local-first memory layer for your AI (Cursor, Zed, Claude)▲36
Hi HN, Working with multiple projects, I got tired of re-explaining our complex multi-node system to LLMs. Documentation helped, but plain text is hard to search without indexing and doesn't work across projects. I built Linggen to solve this. My Workflow: I use the Linggen VS Code extension to "init my day." It calls the Linggen MCP to load memory instantly. Linggen indexes all my docs like it’s remembering them—it is awesome. One click loads the full architectural context, removing the "cold start" problem. The Tech: Local-First: Rust + LanceDB. Code and embeddings stay on your machine. No…
Dec 2025 · github.com
18
Persistent memory for AI coding agents▲4
Open-source MCP server. #5 on LoCoMo. 100% local. MIT.
May 2026 · totalmemory.dev
19
memories.sh▲50
One layer for memories, skills, and rules across any agent
Feb 2026
20TA
TraceMem – A trace-native memory layer for AI agent decisions▲15
Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi
Jan 2026 · tracemem.com
21
Memctl▲4
Shared memory for AI coding agents across your team
Mar 2026
22
YourMemory 2.0▲15
Your AI has the memory of a goldfish. Not anymore
Jul 2026 · yourmemoryai.xyz
23BA
Built a memory layer that stops AI agents from forgetting everything▲13
Tired of AI coding tools that forget everything between sessions? Every time I open a new chat with Claude or fire up Copilot, I'm back to square one explaining my codebase structure. So I built something to fix this. It's called In Memoria. Its an MCP server that gives AI tools persistent memory. Instead of starting fresh every conversation, the AI remembers your coding patterns, architectural decisions, and all the context you've built up. The setup is dead simple: `npx in-memoria server` then connect your AI tool. No accounts, no data leaves your machine. Under the hood it's TypeScript +…
2025 · github.com
24MC
MicroCodex Coding Agent – OpenAI/codex reimplemented in C++ <1MB binary▲19
Aug 2026 · github.com

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