Do I need a database to use Glen?

No. Glen is a managed memory service exposed over MCP. You connect to it as a tool; there is no schema to design, no vector store to run, and no retrieval code to write.

Will it work with my no-code platform?

If your platform supports MCP tools or remote MCP servers, it can connect to Glen with an API key or OAuth and start reading and writing memory immediately.

Shared memory for no-code builders

No-code builders ship real products and automations without writing the plumbing, you assemble apps, workflows, and AI features from visual tools instead of code. But the moment you add an AI step, you hit the same wall engineers do: the model has no memory. Each automation runs stateless, your AI features forget everything between sessions, and the only way to give them recall is to wire up a database, a vector store, and a read/write path, exactly the kind of plumbing no-code is supposed to spare you. Glen, shared memory for AI agents, gives your no-code AI features one durable, org-shared memory through a single MCP tool, no database to manage, no embeddings to maintain.

Glen is a standard MCP server, so any no-code platform that speaks MCP can connect to it as a tool. Once connected, your AI steps can retrieve relevant context and record new facts in a single call. A customer-facing assistant you built without code can pull what your organization already knows about a user before responding; the same flow can write back what it learned so your next automation starts informed. You skip the part where you'd normally have to stand up a database, design a schema, and build embedding and retrieval logic, the hardest, least no-code part of giving AI a memory.

Because Glen is org-scoped, every automation and every AI feature you build shares one memory layer. One tool learns a durable fact; another reads it next time, without you exporting and importing data between apps. And because Glen is a standard MCP server, the memory your no-code tools write is the same memory your team can reach from Claude, Cursor, or any other MCP client, so what your automations learn and what your team knows live in one place. You connect it once with an API key or OAuth and let the memory grow. For builders whose whole philosophy is to avoid undifferentiated plumbing, Glen is the memory layer you don't have to build.

FAQ

Do I need a database to use Glen?: No. Glen is a managed memory service exposed over MCP. You connect to it as a tool; there is no schema to design, no vector store to run, and no retrieval code to write.
Will it work with my no-code platform?: If your platform supports MCP tools or remote MCP servers, it can connect to Glen with an API key or OAuth and start reading and writing memory immediately.