{"id":46981840,"title":"Show HN: MemoryGate – Open-source persistent memory for AI agents via MCP","points":1,"user":"pstryder","time":1770847529,"time_ago":"10 hours ago","type":"link","content":"

I built MemoryGate because I kept watching context vanish.\nI run multiple AI agents across Claude, ChatGPT, and Cursor. Every time a model updated, a platform changed its API, or a context window rolled over — everything the agent had learned was gone. Preferences, decisions, project history, relationship context. Just... wiped.\nThe fundamental problem: AI memory is trapped inside the platform that hosts the conversation. Your agent's knowledge dies with the session, the model version, or the provider's business decisions.\nMemoryGate is a persistent semantic memory layer that sits outside any single model or platform. It connects via MCP (Model Context Protocol), so any MCP-compatible agent — Claude Desktop, ChatGPT, Cursor, custom agents — can store and retrieve memories through a shared, durable knowledge store.\nWhat it actually does:

Semantic memory with vector embeddings — recall by meaning, not keywords\nConfidence-weighted observations that strengthen or decay based on evidence\nAutomatic lifecycle management — high-signal stays hot, noise fades to cold storage\nAppend-only architecture — memories are never overwritten, only superseded with lineage\nKnowledge graphs linking observations, patterns, concepts, and documents\nMulti-tenant with org isolation, roles, and shared memory stores\nOAuth 2.0, audit logs, rate limiting — production infrastructure, not a toy

What it's not:

Not a RAG pipeline. MemoryGate stores what the agent learns from interaction, not document chunks.\nNot prompt injection. Memory lives at the infrastructure layer, not stuffed into system prompts.\nNot tied to any model or provider. Switch from Claude to ChatGPT to a local model — memory persists.

Stack: Python/FastAPI, PostgreSQL + pgvector, Redis, deployed on Railway. MCP-native integration — your agent gets 33 memory tools on connection.\nThe real pitch: Platforms die. Models get deprecated. Context windows roll over. Your AI's memory shouldn't be hostage to your AI's provider.\nOpen source (Apache 2.0), self-hostable, with a hosted SaaS option if you don't want to run infrastructure.

GitHub: https://github.com/PStryder/MemoryGate\nSaaS: https://memorygate.ai\nDocs: https://memorygate.ai/docs/

I'm a solo founder — built this after leaving a decade in enterprise solutions engineering. Happy to answer questions about the architecture, the MCP integration, or why I think persistent memory is the missing infrastructure layer for AI agents.","url":"https://www.memorygate.ai","domain":"memorygate.ai","comments":[],"comments_count":0}