Archiledge is a graph-based Model Context Protocol (MCP) memory server. It provides a structured way for AI agents to store and manage contextual information as entities and relations within a knowledge graph.

How does Archiledge handle data persistence?

Archiledge supports both in-memory storage (default) and Neo4j graph databases for persistence. You can run it with an embedded Neo4j instance (transient or persistent) or connect to an external Neo4j server.

What are Archiledge's main features?

Archiledge offers robust knowledge graph storage, a comprehensive set of MCP tools for creating, reading, searching, and deleting entities and relations, and flexible persistence options including in-memory and Neo4j graph databases.

Is Archiledge suitable for production environments?

No, Archiledge is explicitly designed and optimized for local development and testing environments only. It currently implements no authentication mechanisms and is not recommended for production use in its present state.

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is a specification for how AI models manage and interact with their memory or context. Archiledge provides a concrete, graph-based server implementation of this protocol.

Archiledge

Name: Archiledge
Author: thecookiezen

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Implements a graph-based Model Context Protocol (MCP) memory server.

Archiledge

•

Implements a graph-based Model Context Protocol (MCP) memory server.

Archiledge provides a robust, graph-based implementation of the Model Context Protocol (MCP) Memory Server, designed to serve as a knowledge graph for AI agents. It efficiently stores and manages entities and their relationships, offering a comprehensive set of MCP tools to programmatically create, read, search, and delete graph data. Featuring a modular architecture, Archiledge supports both transient in-memory storage and persistent Neo4j integration, making it an ideal and flexible solution for local development and testing environments that require advanced memory management capabilities for AI applications.

주요 기능

01Knowledge Graph storage for entities and relations

02Support for both in-memory and Neo4j graph persistence

03Optimized for local development and testing environments

040 GitHub stars

05Comprehensive MCP tools for graph manipulation (create, read, search, delete)

06Modular architecture with distinct domain, application, and infrastructure layers

사용 사례

01Developing and testing AI agents requiring memory management

02Prototyping knowledge graph-based applications

03Experimenting with the Model Context Protocol (MCP)

Archiledge

Neon

Figma Context

Magic

Diagram Maker & Visualizer

GH Issues Auto-Fixer

Discord Integration

Archiledge

주요 기능

사용 사례

Neon

Figma Context

Magic

Diagram Maker & Visualizer

GH Issues Auto-Fixer

Discord Integration

주요 기능

사용 사례