fredac100/elasticsearch-memory-mcp

🧠 Elasticsearch-powered MCP server with hierarchical memory categorization, intelligent auto-detection, and batch review capabilities

43
/ 100
Emerging

This tool helps AI developers and prompt engineers manage the 'memory' of AI models, making them more effective and consistent. It takes raw textual information, automatically organizes it into categories like identity or project details, and then provides a structured set of relevant memories for the AI to use. This results in AI models that can maintain context better and respond more appropriately in complex, ongoing interactions.

No commits in the last 6 months. Available on PyPI.

Use this if you are building AI applications or agents and need a robust, persistent way to store, organize, and retrieve specific pieces of information ('memories') for your AI to access.

Not ideal if you don't work with AI models or if you need a simple key-value store without advanced categorization or semantic search capabilities.

AI-memory-management prompt-engineering AI-agent-development contextual-AI AI-workflow-optimization
Stale 6m
Maintenance 2 / 25
Adoption 4 / 25
Maturity 24 / 25
Community 13 / 25

How are scores calculated?

Stars

7

Forks

2

Language

Python

License

MIT

Last pushed

Oct 05, 2025

Commits (30d)

0

Dependencies

5

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