AgenticMaid Project
@Buidl-Land
关于 AgenticMaid Project
AgenticMaid is a Python library designed to interact with one or more Multi-Capability Protocol (MCP) servers.
基本信息
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"
]
}
}
}工具
未检测到工具
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
.envfiles - Supports OpenAI, Anthropic, Azure OpenAI, and local LLMs
- Scheduled tasks with cron-like expressions
- Chat service integration framework
- Agent creation using
langgraphReAct 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
FAQ from AgenticMaid Project
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.
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.
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.
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.
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.
其他 分类下的更多 MCP 服务器
XcodeBuildMCP
cameroncookeA Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.
Awesome Mlops
visengerA curated list of references for MLOps
MCP Go 🚀
mark3labsA Go implementation of the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources and tools.
FastMCP v2 🚀
jlowin🚀 The fast, Pythonic way to build MCP servers and clients.
🪟 Windows-MCP
CursorTouchMCP Server for Computer Use in Windows
评论