@okooo5km
基本情報
A Model Context Protocol server that provides knowledge graph management capabilities.
Create multiple new entities in the knowledge graph
Create multiple new relations between entities
Add new observations to existing entities
Delete multiple entities and their associated relations
Delete specific observations from entities
Delete multiple relations from the knowledge graph
Read the entire knowledge graph
Search for nodes in the knowledge graph based on a query
Open specific nodes in the knowledge graph by their names
Memory MCP Server is a Model Context Protocol server that provides knowledge graph management capabilities, enabling LLMs to create, read, update, and delete entities and relations in a persistent knowledge graph. It is a Swift implementation requiring macOS 14.0 or later, based on the official TypeScript Memory MCP Server.
Install via one-line curl installer or build from source using Swift 6.0+. After installation, configure the server in your MCP client (e.g., Claude.app, Cursor, Chatwise) by specifying the command memory-mcp-server and optionally setting the MEMORY_FILE_PATH environment variable for custom data storage. The server exposes tools such as create_entities, create_relations, search_nodes, and read_graph for knowledge graph operations.
This is a Swift rewrite that requires macOS 14.0 or later, while the TypeScript version supports broader platforms. For Windows, Linux, and macOS 11.0+, a separate Go implementation is available.
You need macOS 14.0 or later, Swift 6.0 or later, and the MCP Swift SDK 0.2.0 or later.
Data is persisted to disk as a line-delimited JSON file. By default it is saved as `memory.json` in the current working directory, but you can customize the path via the `MEMORY_FILE_PATH` environment variable.
Add a `memory` entry under `mcpServers` in your Claude settings with the command `memory-mcp-server` and an optional `MEMORY_FILE_PATH` environment variable.
Persistent memory for AI agents. Hosted MCP server with capsule-scoped key/value storage, tags, TTL expiration, bulk ops, and RBAC.
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors
Ask your Takibi Base collections anything; get answers with cited passages and a support score.
Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.
AI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference
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