Engram is the better fit if
Choose Engram when one managed MCP memory should work across agents, repositories, and teammates, with explicit recovery after context compaction.
Public benchmark
Engram vs AgentMemory
Compare Engram and AgentMemory on public LoCoMo memory tasks. Same-method results are shown where available, with methodology and limitations visible.
Engram92.19%
AgentMemory79.10%
The short answer
AgentMemory is the better fit if
Choose AgentMemory when local-first, open-source coding-agent memory matters more than a managed team service.
What this page does not prove
Retrieval was measured with the same public task. The answer-level comparison is not complete, so we do not infer a score.
What the numbers say
Side by side
+13.09 pp
Engram leads by 13.09 percentage points on R@50.
Not measured here
Not scored under the same answer method
| Decision point | Engram | AgentMemory |
|---|---|---|
| Primary product shape | Managed memory layer for agent teams | Local-first memory for coding agents |
| Delivery model | MCP · Built in | Local CLI, hooks, and MCP |
| Cross-tool agent use | Supported | Supported through MCP and hooks |
| Context-compaction recovery | Built in | Not measured here |
| Team and cross-repo learning | Built in | Not measured here |
| Same-method answer evidence | Supported | Not measured here |
Questions buyers ask
Were Engram and AgentMemory tested the same way?
The values marked as same-method use the same public LoCoMo task, candidate depth, and scoring rule. Product-published numbers from a different protocol are not mixed into this table.
Does the highest retrieval score automatically mean the best product?
No. Retrieval measures whether useful evidence appears in the candidate set. Answer accuracy measures whether that evidence helps produce the right answer. Operations, privacy, integrations, and cost remain separate buying decisions.
Which product should I choose?
Choose Engram for managed workspace memory and team learning. Choose AgentMemory when you prefer a local-first open-source coding-agent stack that you operate yourself.
Engram is measured two ways: first, whether it retrieves the right evidence; second, whether an LLM can answer correctly from that retrieved context.
We keep retrieval and answer accuracy separate. Both use public LoCoMo, but they measure different parts of the memory loop.