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The mnemosyne MCP server was last committed 1mo ago and has 4 contributors. Issue health: 25% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

mnemosyne MCP Server

Name: 28naem-del/mnemosyne
Rating: 3.4 (1 reviews)
Author: 28naem-del

28naem-del/mnemosyne

Score: 59.9 Rank #6345 Agent Framework

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Evidence-backed memory for AI agents: local-first recall, temporal history, tested skills, and gradual migration.

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Overview

28naem-del/mnemosyne is a TypeScript tool licensed under MIT. Evidence-backed memory for AI agents: local-first recall, temporal history, tested skills, and gradual migration. Topics: agents, ai, ai-agents, artificial-intelligence, cognitive, embeddings, knowledge-graph, llm, machine-learning, memory, multi-agent, typescript, vector, memory-migration, model-context-protocol, sqlite.

Ranked #6345 out of 24846 indexed tools.

Ecosystem

TypeScript MIT

agentsaiai-agentsartificial-intelligencecognitiveembeddingsknowledge-graphllmmachine-learningmemorymulti-agenttypescriptvectormemory-migrationmodel-context-protocolsqlite

Score Breakdown

Stars 15% 150

150 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 25%

3/12 issues closed → many open issues

Contributors 10% 4

4 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 14

Description Good

License MIT

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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Freshness high impact

Last commit was 50 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 9 open vs 3 closed issues — triaging stale issues improves health

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Details

Stars: 150
Forks: 14
Open Issues: 9
Closed Issues: 3
Contributors: 4
Dependents: —
Language: TypeScript
License: MIT
Last Commit: 1mo ago

Matched Queries

topic:model-context-protocol

From the README

# Mnemosyne

**The next agent starts wiser.**

Persistent memory for AI agents that need to carry work forward, recover original evidence, and stop following a lesson when its source changes.

Mnemosyne connects memory to its consequences: a corrected requirement can retire a dependent procedure, a failed trial can withhold a skill, and a new agent can resume from an explicit handoff. Run the local engine in one SQLite file; connect your host through TypeScript, MCP, CLI, or authenticated HTTP with a Python client and live inspector.

**2.0.0-rc.9 · Release candidate · MIT · Node.js ≥22.16**

[Website](https://mnemosy.ai) · [Quickstart](docs/quickstart.md) · [Documentation](docs/README.md) · [Examples](examples/README.md) · [Migration](docs/BRIDGE.md) · [Measured results](docs/evaluation/BENCHMARKS.md) · [npm](https://www.npmjs.com/package/mnemosy-ai/v/2.0.0-rc.9) · [Contributing](CONTRIBUTING.md)

## Choose your engine

**Both engines ship in 2.0.0-rc.9.** Choose the storage and runti

Read full README on GitHub →