Persistent Memory for AI Agents with Sutra MCP: Private, Portable, and Reusable
Your AI agent understands the project today. Tomorrow, you open another agent and explain the same architecture, preferences, and decisions again. The model changed. The chat history stayed behind. Your context did not move with you. I built Sutra MCP to make that handoff explicit: one private, portable memory layer and reusable skill library that can be accessed by supported AI agents through…
Sutra MCP is a hosted service that provides AI agent memory and reusable skills. Unlike normal conversations, Sutra allows users to explicitly save memories and retrieve them when needed. The memory layer stores durable facts, preferences, corrections, and decisions, while the skill library contains reusable operating knowledge in the form of SKILL.md workflows.
Sutra keeps both memory and skills separate, allowing users to share and reuse them across different AI agents without permanently injecting everything into every prompt. To connect an MCP client, users need to create a Sutra account and choose an authentication method supported by their client. Authentication options include OAuth 2.1 for remote MCP clients with browser authorization, API key for clients expecting an Authorization header, and Cursor with OAuth for clients using .cursor/mcp.json.
Once the client is authenticated, users can perform various actions such as saving deliberate project decisions, retrieving memories from specific clusters, and loading reusable skills only when needed. This approach ensures that only relevant and intentional information is stored and retrieved, enabling seamless handoffs between AI agents while maintaining privacy and portability.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
