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AgenticMaid Project MCP Server

@Buidl-Land

代码仓库

基本信息

分类

其他

许可证

Apache-2.0 license

传输方式

stdio

作者

Buidl-Land

关于 AgenticMaid Project MCP Server

AgenticMaid is a Python library designed to interact with one or more Multi-Capability Protocol (MCP) servers.

#agenticmaid#mcp#python-library

AgenticMaid Project 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": {
    "AutoMaid": {
      "command": "python",
      "args": [
        "-m",
        "uvicorn",
        "AgenticMaid.api:app",
        "--reload"
      ]
    }
  }
}

AgenticMaid Project 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 AgenticMaid Project?

AgenticMaid Project is a Python library that interacts with one or more Multi-Capability Protocol (MCP) servers. It dynamically fetches tools from those servers, manages configurations for various AI/LLM services, schedules automated tasks, and handles chat service interactions. It is designed for developers building AI-powered applications that need to combine multiple capabilities and language models.

How to use AgenticMaid Project?

Install the required dependencies (python-dotenv, langchain-mcp-adapters, langgraph, etc.) and configure the library using either a Python dictionary, a JSON file, or a .env file for API keys. Instantiate ClientAgenticMaid with your configuration, call await client.async_initialize(), then use run_mcp_interaction() to invoke agents that leverage the fetched MCP tools.

Key features of AgenticMaid Project

  • Multi-server MCP interaction and tool fetching
  • Dynamic tool retrieval at runtime
  • Flexible configuration via dictionary, JSON, or .env files
  • Supports OpenAI, Anthropic, Azure OpenAI, and local LLMs
  • Scheduled tasks with cron-like expressions
  • Chat service integration framework
  • Agent creation using langgraph ReAct agents

Use cases of AgenticMaid Project

  • Building AI agents that use tools from multiple MCP servers
  • Scheduling periodic automated tasks (e.g., hourly summaries)
  • Powering chat interfaces with configurable AI/LLM backends
  • Rapidly prototyping applications that need to switch between AI providers

常见问题

1

What are the system requirements?

Python 3.8 or higher is required. The library depends on packages such as `langchain-mcp-adapters`, `langgraph`, `schedule`, and provider-specific packages like `langchain-openai` and `langchain-anthropic`.

2

How do I configure API keys for AI services?

API keys and default model settings can be placed in a `.env` file inside the `AgenticMaid/` directory. They can be overridden by values passed directly in the main JSON or dictionary configuration.

3

Can AgenticMaid connect to multiple MCP servers at the same time?

Yes. The library is designed to connect to multiple MCP servers and dynamically fetch and combine their tools for use by agents.

4

What AI providers are supported?

OpenAI, Anthropic, Azure OpenAI, and local OpenAI-compatible servers (e.g., LM Studio) are supported. Providers are configured under the `ai_services` section of the configuration.

5

How do I run a scheduled task?

Define the task in the `scheduled_tasks` array of the configuration, providing a `cron_expression` (e.g., `"0 * * * *"`), a `prompt`, and a `model_config_name`. The schedule is handled by the `schedule` library.

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