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Memory Cloud Protocol (MCP) Server

@OutCorp

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

OutCorp

关于 Memory Cloud Protocol (MCP) Server

MCP Server created with cursor.ai

Memory Cloud Protocol (MCP) Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-outcorp": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-server",
        "."
      ]
    }
  }
}

Memory Cloud Protocol (MCP) Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Memory Cloud Protocol (MCP) Server?

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.

How to use Memory Cloud Protocol (MCP) Server?

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.

Key features of Memory Cloud Protocol (MCP) Server

  • Persists memory records for Supabase projects including UUIDs, table names, RLS states, and keys
  • Stores API tokens, project states, and function deployment metadata
  • Logs agent tasks and output
  • Provides automatic lookup of known entities to prevent repetitive errors
  • Exposes REST endpoints for memory management and agent coordination

Use cases of Memory Cloud Protocol (MCP) Server

  • Maintaining persistent context for AI agents across sessions
  • Coordinating agent actions through dispatch instructions
  • Logging and reviewing agent errors and task outputs

常见问题

1

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.

2

What runtime dependencies are required?

Node.js is required. After cloning, run `npm install` to install dependencies. A Supabase project with the required tables must be available.

3

Where does data persist?

All memory records, logs, and dispatches are stored in the Supabase PostgreSQL database you configure.

4

How is the server deployed?

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`).

5

What authentication is used?

Most REST endpoints require an `MCP_API_KEY` for authentication. The `/health` endpoint is public and does not require authentication.

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