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Assistant MCP Server

@nodlab

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT

传输方式

stdio

作者

nodlab

关于 Assistant MCP Server

MCP server for productive development

Assistant 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-assistant-local": {
      "command": "npx",
      "args": [
        "tsx",
        "/path/to/folder/src/index.ts"
      ],
      "env": {
        "TOOLS_PATH": "/path/to/folder/tools.json"
      }
    }
  }
}

Assistant 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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Assistant MCP Server?

An MCP server that provides tools for retrieving project architecture information, searching tasks, and generating optimized prompts for AI models. It is designed for developers working on frontend applications who need to integrate structured project data into AI workflows.

How to use Assistant MCP Server?

Install dependencies with yarn install, then build with yarn build. Add a tools.json file defining the available tools. To run locally, configure an MCP client with the command npx tsx /path/to/src/index.ts and set the TOOLS_PATH environment variable to the path of tools.json.

Key features of Assistant MCP Server

  • Provides three pre‑defined tools: architecture_info, search_tasks, and optimize_prompt.
  • Uses a tools.json configuration file for tool definitions.
  • Supports file‑based plugins (e.g., reading architecture info and tasks from local files).
  • Includes a promptOptimizer plugin for generating final structured AI prompts.
  • Runs locally via npx tsx for easy development and testing.

Use cases of Assistant MCP Server

  • Automatically retrieve frontend project architecture before implementing new tasks.
  • Collect project tasks from a tasks.txt file and guide AI to execute them according to architecture.
  • Generate a final, structured prompt by combining multiple context sections and instructions for an AI model.

常见问题

1

What dependencies are required?

The server requires Node.js and TypeScript (via `tsx`). Dependencies are installed with `yarn install`.

2

How do I configure the tools?

Create a `tools.json` file at the project root with an array of tool objects. Each tool specifies its name, description, input schema, and plugin configuration (e.g., `file` or `promptOptimizer`).

3

Where is the data stored?

Tool data resides in local files as specified in the plugin arguments (e.g., `architecture.md` and `tasks.txt`). The server reads these files at runtime.

4

What transport does Assistant MCP Server use?

The server uses standard MCP stdio transport – it is invoked as a command‑line process via `npx tsx`.

5

Is there any authentication or security mechanism?

The README does not mention any authentication. The server runs locally and relies on file‑system access to the configured paths.

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