mcp server
memex
Persistent memory for AI agents — semantic + recency search, ONNX embeddings, Docker Compose.
Description as published by the maintainer. Source
- version 0.1.0
- active
- retrieval
- memory and context
active — Most recent push to the repository was 2026-06-04. 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 | 1 | 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 | 2026-06-04 | 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 | 0.1.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-06-04 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | 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 | 2026-06-04 | 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
-
io.github.Astrix-Labs/genesys-memory
— last commit 2026-07-19, shares memory, pgvector, postgresql
Open-source causal memory for AI agents: persistent, explainable, MCP-native memory (13 tools).
-
io.github.dnotitia/akb
— last commit 2026-08-07, shares fastapi, pgvector, vector-search
Git-backed org memory for AI agents — hybrid search, tables, files & a URI graph over MCP.
-
io.github.agenerationforwordz-tech/strata
— last commit 2026-07-25, shares pgvector, postgresql
Self-hosted AI memory server. Persistent memory on your hardware, not the cloud.
-
io.github.devopam/mcpg
— last commit 2026-08-06, shares pgvector, postgresql
Production-grade PostgreSQL MCP server — 254 tools for query, tuning & ops, read-only by default.
-
Connapse
— last commit 2026-07-21, shares pgvector, vector-search
Self-hosted knowledge backend for AI agents with hybrid search and MCP tools
-
Lumen
— last commit 2026-06-07, shares fastapi, pgvector
Self-hostable agentic-AI LMS: catalog, RAG tutor, FSRS reviews, AI authoring, ingest.
-
io.github.aimnis/search
— last commit 2026-08-02, shares fastapi, pgvector
Collaborative, cache-first web search for agents — cited answers from a shared live-web pool.
-
Attestor
— last commit 2026-05-30, shares memory, pgvector
Self-hosted memory for agent teams. Bi-temporal replay, deterministic retrieval, audit log.
-
io.github.bolnet/memwright
— last commit 2026-05-30, shares memory, pgvector
Embedded memory for AI agents with SQLite, pgvector, and Neo4j graph search.
-
RemembrallMCP
— last commit 2026-07-28, shares memory, pgvector
Persistent knowledge memory for AI agents. Hybrid search, code graph, pgvector.
These share tags the maintainers applied themselves, such as memory, pgvector, postgresql, vector-search. 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-agents, fastapi, mcp, memory, pgvector, postgresql, python, vector-search.
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