Why not just build a memory layer myself?

You can, but it's a real ongoing project: schema, embeddings, retrieval quality, evals, and maintenance. Glen is that layer as a managed MCP server, so you spend your time on product instead.

How does Glen scale as my team grows?

Glen is org-scoped from day one. New hires' agents inherit all accumulated memory automatically, and every MCP client your team adopts reads and writes the same store.

Shared memory for technical founders

As a technical founder you're the architect, the first engineer, and increasingly the person directing a fleet of AI agents across your codebase and your business. You feel the cost of agent amnesia more acutely than most: every session your coding agent re-learns the system you designed, every automation forgets the context you gave it, and the institutional knowledge that lives in your head never makes it into the tools building your company. Rolling your own memory layer is a real project, schema, embeddings, retrieval, eval, and it competes directly with shipping product. Glen, shared memory for AI agents, gives every agent in your org one durable, shared memory through a single MCP tool, so the knowledge compounds instead of evaporating.

Wire Glen in as an MCP tool and every agent you run, coding, support, ops, research, can retrieve relevant org context and record what it learns in one round trip. The agent working on your payments module recalls the constraints and decisions behind it instead of rediscovering them; the agent answering a customer pulls what's already known about that account; a research agent writes back a finding that your product agent reads next week. You stop building memory infrastructure as a side quest and get back to the architecture and product work only a founder can do.

Because Glen is org-scoped, the memory is the company's, not any one agent's or any one tool's. As you hire, every new engineer's agents inherit the accumulated knowledge automatically, no onboarding doc to write, no per-person memory to seed. The decisions you make today become context your future team's agents read by default. And because Glen is a standard MCP server, the same store is reachable from Claude Code, Cursor, your CI agents, and your production automations, so the knowledge your company generates lives in one place rather than scattered across silos. You connect it once over OAuth or an API key and treat memory as infrastructure you no longer have to own. For a founder optimizing for leverage, Glen turns a fleet of forgetful agents into a team with shared institutional memory.

FAQ

Why not just build a memory layer myself?: You can, but it's a real ongoing project: schema, embeddings, retrieval quality, evals, and maintenance. Glen is that layer as a managed MCP server, so you spend your time on product instead.
How does Glen scale as my team grows?: Glen is org-scoped from day one. New hires' agents inherit all accumulated memory automatically, and every MCP client your team adopts reads and writes the same store.