MCP server for 0Latency — persistent memory layer for AI agents. Give Claude, Cursor, or any MCP client long-term memory.
Free
Nothing to run from here
Engram Rs is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
Open Installation—
p95 latency
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call success
local
runs on your machine
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calls last 7d
What it does
MCP server for engram — hierarchical memory engine for AI agents
Quickstart
# 1 — run it from where its publisher ships it
npx -y engram-rs-mcp
# 2 — ask your agent something
> MCP server for engram — hierarchical memory engine for AI agents
Engram Rs is free: there is no plan to choose, no cap to set and nothing that can bill you.
Publishernot claimed
KAAll 1 server
kael-bit1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Engram Rs as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. It is scanned, signed and pinned to the version you choose — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. Claude Code registers it in one command.
claude mcp add engram-rs-mcp -- npx -y engram-rs-mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free to install, and it runs from its publisher’s own package: no account, no key, no card.
What it writes
One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
16 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Store a memory. All memories start in Buffer and promote to Working/Core through
Takes no parameters.
Example callreturns →
Hybrid semantic + keyword search with budget-aware retrieval.
Takes no parameters.
Example callreturns →
List recent memories by creation time. Good for session context recovery.
Takes no parameters.
Example callreturns →
Full memory bootstrap for session recovery. Returns core (permanent knowledge),
Takes no parameters.
Example callreturns →
Extract structured memories from raw text using LLM.
Takes no parameters.
Example callreturns →
Quick keyword search. Lighter than recall — no scoring or budget logic.
Takes no parameters.
Example callreturns →
Run a memory consolidation cycle. Promotes important memories upward,
Takes no parameters.
Example callreturns →
Get memory statistics: counts per layer, AI status, version.
Takes no parameters.
Example callreturns →
Repair FTS search index. Removes orphaned entries and rebuilds missing ones.
Takes no parameters.
Example callreturns →
Detailed health check: uptime, RSS memory, embed cache stats, AI config status.
Takes no parameters.
Example callreturns →
Fetch trigger memories for a specific action. Call before performing an action (e.g. git-push, deploy) to recall relevant lessons and rules.
Takes no parameters.
Example callreturns →
Delete a memory by ID. Use when a memory is outdated, incorrect, or redundant.
Takes no parameters.
Example callreturns →
Update a memory
Takes no parameters.
Example callreturns →
List soft-deleted memories. Recently deleted items can be restored.
Takes no parameters.
Example callreturns →
Restore a soft-deleted memory from trash back to its original layer.
Takes no parameters.
Example callreturns →
Drill into topic clusters by ID. Use after /resume to explore specific topics from the knowledge index.
Takes no parameters.
Example callreturns →
Freeyour plan
$0 forever
- Every tool, no call limit
- No card, no account needed
- Source published under a licence you can read
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because nothing bills
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable. Engram Rs costs nothing to install and nothing to call, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
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Alert at 80% · then the tool returns a normal MCP error
Used this month: $8.42
$16.58 left
ATrust score 96 / 100
Release 0.14.0 · scanned 25 Aug 2026
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
Threat score100
Client score96
Findings0 threat · 0 capability
Capabilitymoderate
Coveragesource
Verificationrepo
Surface digest2ceb6c5038a2f16d11b0ba771c67a213fd12d4c2f3122795370190cd3c550b90
Score vectorthreat 100 → client 96
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | moderate | capability blast radius (moderate) — client exposure if the model is manipulated | −3 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (16 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. moderate is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| engram_store | no tags | |
| engram_recall | no tags | |
| engram_recent | no tags | |
| engram_resume | no tags | |
| engram_extract | no tags | |
| engram_search | no tags | |
| engram_consolidate | no tags | |
| engram_stats | no tags | |
| engram_repair | no tags | |
| engram_health | untrusted-input | |
| engram_triggers | untrusted-input | |
| engram_delete | no tags | |
| engram_update | no tags | |
| engram_trash | no tags | |
| engram_restore | no tags | |
| engram_topic | no tags |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
Integrityfirst-seen
Surface digest2ceb6c5038a2f16d
Scanned2026-08-25
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Pinned to 0.14.0 — the install command below asks for that release. A pin is part of an install, so it is kept for this visit and written down when you install.
0.14.0
undated
installedNo release note was published with this version.
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no reviews yet
Reviews are earned
Only accounts with at least 50 real tool calls against this server in the last 90 days can post. Ratings are weighted by how much the reviewer actually uses it, and publishers can reply once per review.
Reviews are earned
Writing one takes an account with at least 50 real tool calls against Engram Rs in the last 90 days. That is the whole gate — there is no other way to post, which is why the counts beside each review are worth reading.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes an account with 50 real tool calls against it.