io.github.ayushagrawal288/memex

MCPcommunity
v0.1.0io.github.ayushagrawal288UnknownUpdated 4mo agoGitHub

Persistent memory for AI agents — semantic + recency search, ONNX embeddings, Docker Compose.

A production-grade persistent memory service for AI agents. Agents forget everything between sessions by default — memex fixes that. It stores, retrieves, and ranks conversation memory using semantic search with recency decay, so agents surface what's relevant and recent, not just what's semantically closest. Write path: content → fastembed ONNX inference (local, ~12 ms CPU, ) → INSERT with…

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1GitHub stars
4mo agoLast update
Package
Authorio.github.ayushagrawal288
LicenseUnknown
Version0.1.0
Sourcemcp-registry
Trust Status
B
60/100Good
✓Listed in Forge index+10/10
—Publisher identity verified+0/30
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—Domain verification+0/10
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✓Prompt-injection scan · clean+30/30
✓Obfuscation / exfil scan · clean+20/20
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StatusCommunity-indexed
PublisherUnverified
SignatureUnsigned
Domain—
Provenance—
DependenciesNot audited
Tool surface—
Security scan✓ CleanvHEAD · 3mo agoHow well does this scan work?
EvalsNone
IndexedJun 13, 2026

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Tools

No tool declarations found in the source3mo ago

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About

A production-grade persistent memory service for AI agents. Agents forget everything between sessions by default — memex fixes that. It stores, retrieves, and ranks conversation memory using semantic search with recency decay, so agents surface what's relevant and recent, not just what's semantically closest. Write path: content → fastembed ONNX inference (local, ~12 ms CPU, ) → INSERT with 384-dim vector → return memory ID. Read path: query → embed → pgvector cosine search (topk × 3…

Keywords
mcp
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