Glen

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Shared memory for Letta

Letta (formerly MemGPT) is built around the idea that agents should have memory, with a clever architecture for managing what stays in context and what gets paged to a longer-term store. Letta even supports shared memory blocks, so multiple Letta agents can read and write the same block. But that sharing stays inside Letta: there is no built-in way for agents on other frameworks, or your other MCP tools, to draw on one organizational source of truth. Glen, shared memory for AI agents, complements Letta by adding an org-scoped memory layer over MCP, so many Letta agents, and the rest of your stack, can read from and write to one shared store.

Letta is excellent at managing a single agent's working and archival memory. Glen solves a different problem: the knowledge that should be shared across agents and across frameworks. Expose Glen to your Letta agents as an MCP tool and any agent can call it to retrieve what the organization already knows and to record durable facts that other agents, not just itself, will see. Letta keeps doing what it does well for each agent's own state; Glen becomes the common ground between them.

Because Glen is org-scoped, a fact one Letta agent learns is immediately available not just to other Letta agents but to any other MCP client and framework, instead of staying inside Letta. That is the gap Letta's own sharing leaves: cross-framework, cross-client knowledge. A support agent records a durable customer constraint; a separate analysis agent, or a human in Claude Code or Cursor, reads it next time. And because Glen speaks standard MCP, you do not have to bridge memory formats between frameworks, the same store is reachable from anywhere that speaks MCP. Wire it in once over OAuth or an API key and let your Letta fleet share one growing memory instead of many isolated ones.

FAQ

Does Glen conflict with Letta's own memory system?
No. Letta manages each agent's memory and can share blocks between Letta agents; Glen adds an org-shared store reachable over MCP from any framework or client. They are complementary, Letta within its own runtime, Glen across all of them.
How do Letta agents use Glen?
Connect Glen as an MCP tool. Any Letta agent can then call it to retrieve org-shared context and write observations that every other agent and MCP client can read.