What database does Memory Cloud Protocol (MCP) Server use?
The server uses Supabase/PostgreSQL. You must create three tables (`memory`, `logs`, and `dispatches`) along with a UUID extension in your Supabase project.
@OutCorp
基本情報
MCP Server created with cursor.ai
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": {
"mcp-server-outcorp": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-server",
"."
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
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。
Memory Cloud Protocol (MCP) Server is a backend service for persisting and coordinating agent memory, designed for use with AI agents such as Cursor. It stores memory records, API tokens, project states, and function deployment metadata in a Supabase/PostgreSQL database, providing automatic entity lookup and REST endpoints for agent coordination.
Clone the repository, install dependencies with npm install, copy .env.example to .env, set up a Supabase project with the required tables, then start the server using npm run dev (development) or npm start (production). Use the provided test scripts (test-local.sh, test-railway.sh) to verify health endpoints and authentication.
The server uses Supabase/PostgreSQL. You must create three tables (`memory`, `logs`, and `dispatches`) along with a UUID extension in your Supabase project.
Node.js is required. After cloning, run `npm install` to install dependencies. A Supabase project with the required tables must be available.
All memory records, logs, and dispatches are stored in the Supabase PostgreSQL database you configure.
It is designed for Railway.app deployment using a Dockerfile and `railway.json` configuration. The server can also be run locally with Docker (`docker build -t mcp-server` then `docker run -p 3002:3002 --env-file .env mcp-server`).
Most REST endpoints require an `MCP_API_KEY` for authentication. The `/health` endpoint is public and does not require authentication.

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