The self‑governing memory layer for agents
One MCP server connection.
Engrammic remembers, recalls, traces, and synthesizes relevant context for your agents while you prompt.
memory is flat. meaning is engrammic.
THE PROBLEM
Chat compaction, RAG, and LLM Wiki all hit the same wall.
Scalability issues
Old files quickly become stale. 100 files? Manageable; 5k files? Noise that burn tokens & confuses agents.
Provenance gap
Retrieves what is semantically close, not what was concluded; breaks down when asked how it got there.
Lost nuance
Context window filled, sessions compact. Five compactions later, important nuance & intent lost.
Confidence decay
Old and new “facts” sit side by side with the same confidence, so you stop trusting what it remembers.
Solving memory takes time away from building. Performance, scalability and provenance needs good design philosophy.
the wager
Context rot is what kills agents. Self-governing memory let agents scale.
memory that compounds, with receipts.
automatic remember & recall.
No repasting context. Your agent pulls what it already knows about this topic and adds today's conclusion, automatically.
→ fewer tokens · same answer
answers with cited sources.
Every claim links back to the observations that support it. Ask "why?" and the agent walks you down the chain.
→ reliable answers with provenance
supersede & synthesize.
Contradictions don't pile up. Engrammic merges conflicting positions by source quality, replaces the outdated, and keeps one true answer.
→ one source of truth · not three
how to use
one MCP server. every agent.
Install once. Your agents share memory across sessions, projects, and tools. That's the whole setup.
curl -fsSL https://get.engrammic.ai | sh
claude mcp add engrammic --transport http https://beta.engrammic.ai/mcp/
benchmarks
we measure what actually compounds.
Making LLMs understand financial documents better
Benchmark in progress. We're running Engrammic against SEC filing QA on our internal harness. Full results coming soon.
in progress
faq
questions, answered.
Shared agent memory with evidence. Agents store observations, attach claims to sources, and recall structured knowledge across sessions and tools. One MCP server, no raw dumps.
invitation
waitlist over, try it out!
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