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AI Meta MCP Server

@alxspiker

代码仓库

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

alxspiker

关于 AI Meta MCP Server

A dynamic MCP server that allows AI to create and execute custom tools through a meta-function architecture

#ai-meta-mcp-server#dynamic-tools#meta-function-architecture

AI Meta 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": {
    "ai-meta-mcp-server": {
      "command": "npx",
      "args": [
        "ai-meta-mcp-server"
      ]
    }
  }
}

AI Meta 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 AI Meta MCP Server?

AI Meta MCP Server is a dynamic MCP (Model Context Protocol) server that allows AI models to create and execute their own custom tools at runtime. It provides a meta-function architecture enabling AI to extend its own capabilities by defining custom functions. This server is designed for developers and AI systems that need flexible, on-the-fly tool creation within a secure environment.

How to use AI Meta MCP Server?

Install via npm: npm install ai-meta-mcp-server. Run with npx ai-meta-mcp-server or with Docker. Configure behavior using environment variables (e.g., ALLOW_JS_EXECUTION, ALLOW_PYTHON_EXECUTION, PERSIST_TOOLS). For Claude Desktop, add the server to claude_desktop_config.json with command npx -y ai-meta-mcp-server and desired env settings.

Key features of AI Meta MCP Server

  • Dynamic tool creation by AI models at runtime
  • Multiple runtime environments: JavaScript, Python, Shell
  • Sandboxed security for tool execution
  • Persistent storage of custom tool definitions
  • Flexible tool registry for managing, listing, updating, deleting tools
  • Human approval flow for tool creation and execution

Use cases of AI Meta MCP Server

  • AI assistants creating custom calculation tools on demand
  • Extending AI capabilities with user-defined functions at runtime
  • Running code in isolated sandboxes for safe experimentation
  • Persisting custom tools across sessions for repeated use

常见问题

1

What runtime environments are supported for tool execution?

JavaScript, Python, and Shell execution are supported, configurable via environment variables (default: JS enabled, Python and Shell disabled).

2

How are tools secured?

All code executes in sandboxed environments. Human approval is required for tool creation and execution. Tool execution privileges are configurable via environment variables, and audit logging tracks all operations.

3

Can tools be persisted between sessions?

Yes, by default tools are saved to a JSON database (`TOOLS_DB_PATH`). Set `PERSIST_TOOLS=true` to enable persistence.

4

How do I run the server?

Install via npm and run with `npx ai-meta-mcp-server`, or run with Docker using the provided Dockerfile. The server communicates via MCP stdio transport.

5

What is the purpose of this server?

It allows AI models to dynamically create and execute custom tools, extending their own capabilities through a meta-function architecture, while maintaining safety through sandboxing and human approval.

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