mcp server
com.memxus/memxus
Persistent memory layer that saves and recalls your project context and preferences.
Description as published by the maintainer. Source
- version 1.3.2
- active
- memory and context
active — Most recent push to the repository was 2026-07-30. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 3 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-07-30 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.3.2 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-30 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | AGPL-3.0 | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-30 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
Synap Memory
— last commit 2026-08-06, shares ai-memory, memory, memory-layer
Persistent memory for AI agents — log and recall conversation context over MCP.
-
io.github.aayoawoyemi/ori-memory
— last commit 2026-07-30, shares ai-memory, memory, persistent-memory
Persistent memory infrastructure for AI agents. Identity, knowledge graph, and search.
-
coldstart
— last commit 2026-08-06, shares memory, persistent-memory
Codebase memory for AI agents: an AST index plus agent-written notes that self-stale.
-
Zikkaron
— last commit 2026-04-01, shares memory, persistent-memory
Biologically-inspired persistent memory engine for Claude Code MCP agents
-
io.github.archetypal-ai/archetypal-ai
— last commit 2026-03-24, shares memory, persistent-memory
Persistent memory for AI agents. recall, remember, checkpoint — soul preservation.
-
hmem — Humanlike Memory for AI Agents
— last commit 2026-07-21, shares memory, persistent-memory
Persistent 5-level hierarchical memory for AI agents. SQLite-backed, lazy-loaded.
-
io.github.cdeust/hypermnesia-mcp
— last commit 2026-08-06, shares memory, persistent-memory
Persistent memory for Claude — 36 cited neuroscience mechanisms, local-first, hybrid retrieval.
-
CPersona
— last commit 2026-08-06, shares memory, persistent-memory
Persistent AI memory in one SQLite file: 3-layer hybrid search, confidence scoring, 29 tools.
-
Talamus
— last commit 2026-08-05, shares ai-memory, persistent-memory
Local-first, source-grounded memory that survives AI agent sessions.
-
io.github.cachly-dev/mcp-server
— last commit 2026-08-05, shares ai-memory, persistent-memory
Persistent memory + causal root-cause analysis for AI coding agents. 126 MCP tools. EU, GDPR.
These share tags the maintainers applied themselves, such as ai-memory, memory, memory-layer, persistent-memory. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai, ai-memory, ai-persistence, memory, memory-layer, persistent-memory.
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
Join ZBS AI Practice Lab