EMMS - Enhanced Memory Management System
@supermaxlol
EMMS - Enhanced Memory Management System について
Cognitive memory system for AI agents with 129 MCP tools. Persistent hierarchical memory, emotional recall, knowledge graphs, spreading activation, hybrid retrieval (BM25+RRF), metacognition, goal tracking, spaced repetition, dream consolidation, and more.
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"emms": {
"command": "uvx",
"args": [
"emms-mcp"
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is EMMS - Enhanced Memory Management System?
EMMS is a cognitive memory system for AI agents, providing 129 MCP tools for storage, retrieval, knowledge graphs, reflection, and metacognition. It is available under the MIT License and can be installed via pip, npx, or uvx.
How to use EMMS - Enhanced Memory Management System?
Install the package using pip install emms-mcp, npx -y emms-mcp, or uvx emms-mcp. Configure it in an MCP client by adding a server entry with command uvx and args ["emms-mcp"]. The server exposes 129 tools across categories like Storage, Retrieval, Knowledge Graph, Reflection, Emotions, Goals, Metacognition, Memory Management, Identity, Prediction, and Multi-Agent.
Key features of EMMS - Enhanced Memory Management System
- Provides 129 MCP tools for cognitive memory tasks
- Supports hybrid and associative retrieval methods
- Includes knowledge graph building and analysis tools
- Offers reflection and dream-like synthesis capabilities
- Tracks emotional states and mood trends
- Enables multi-agent memory merging and migration
Use cases of EMMS - Enhanced Memory Management System
- AI agents maintaining long-term memory across sessions
- Building and querying knowledge graphs from stored information
- Performing metacognitive analysis and bias detection
- Coordinating shared memory across multiple AI agents
- Enabling adaptive retrieval based on context and affect
FAQ from EMMS - Enhanced Memory Management System
What platforms or runtimes does EMMS require?
It requires a Python environment (via pip) or Node.js (via npx), and can also be run via uvx. It must be used with an MCP-compatible client.
What types of memory operations does it support?
It supports storing, retrieving, decaying, deduplicating, and reconsolidating memories, along with advanced retrieval like hybrid, adaptive, and affective retrieval.
Can EMMS be used with multiple AI agents?
Yes, it includes multi-agent tools such as merge_from, list_namespaces, and migrate_namespace for sharing or moving memory between agents.
Does it support emotional modeling?
Yes, it provides tools for managing current emotion, regulating emotions, tracking mood trends, and viewing the emotional landscape.
Is there any built-in reflection or self-improvement?
Yes, the Reflection category includes reflect, dream, synthesize_wisdom, and abstract_principles tools, along with metacognitive reports and consciousness metrics.
「メモリとナレッジ」の他のコンテンツ
Solomd
zhitongblogA markdown editor — and the bridge to your LLM. Local-first, MIT, ~15 MB. Bundled MCP server lets Claude Code / Codex / Cursor drive your vault directly. 14 AI providers BYOK.
Notion MCP Server
awkoyNotion MCP server for Claude, Cursor, ChatGPT & Claude Desktop. Connect AI agents to Notion via Model Context Protocol — pages, databases, blocks, comments, files.
Docs MCP Server
araboldGrounded Docs MCP Server: Open-Source Alternative to Context7, Nia, and Ref.Tools
Basic Memory
basicmachines-coAI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: https://discord.gg/tyvKNccgqN
RAG Documentation MCP Server
hannesrudolphAn MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
コメント