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superlocalmemory MCP Server

qualixar/superlocalmemory

Score: 82.9 → 0% Rank #1321 Search & RAG
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Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253

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Overview

qualixar/superlocalmemory is a Python tool licensed under AGPL-3.0. Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253 Topics: knowledge-graph, local-first, agent-memory, agent-reliability, ai-agents, claude-code, cursor, llm-memory, mcp, mcp-server, persistent-memory, qualixar, semantic-search, vector-search, windsurf.

Ranked #1321 out of 24846 indexed tools.

In the top 6% of all indexed tools.

Has 10 contributors.

Ecosystem

Python AGPL-3.0 117 pypi/wk
knowledge-graphlocal-firstagent-memoryagent-reliabilityai-agentsclaude-codecursorllm-memorymcpmcp-serverpersistent-memoryqualixarsemantic-searchvector-searchwindsurf

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 232

232 stars → growing community

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 96%

68/71 issues closed → responsive maintainer

Contributors 10% 10

10 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads 13% 117/wk

117 weekly installs → early adoption

Forks 36
Description Good
License AGPL-3.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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AgentRank score for qualixar/superlocalmemory
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Matched Queries

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From the README

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# SuperLocalMemory: governed, local-first memory for AI agents

Claude Code, Codex, Cursor and other MCP clients forget what they learned when a session ends. SuperLocalMemory (SLM) gives them one long-term memory that lives on your machine: it learns from use, enforces who may read and erase what, coordinates many agents, and says "I don't have that" instead of guessing.

**Every recall is checked before your agent uses it.** A judge decides whether the memories found actually answer the question: **Laya** runs fully on your Mac, and **Jev** runs online on Windows, Linux and macOS. When they don't answer it, SLM says so instead of handing over a confident wrong answer: a hallucination guard for retrieval ([answer check](#answer-check-laya-and-jev)).

In Mode A, core remember and recall make no model-provider call. Anything that sends d
Read full README on GitHub →

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