Agribrain Mcp
What is Agribrain Mcp
AgriBrain_MCP is an intelligent brain framework designed for smart agriculture, integrating various AI capabilities to enhance automation and intelligence in agricultural production through workflow orchestration, service deployment, and tool encapsulation.
Use cases
Use cases for AgriBrain_MCP include diagnosing pest issues through multi-turn interactions, providing real-time weather and environmental data, and assisting in crop growth monitoring and nutrient management.
How to use
To use AgriBrain_MCP, install the required dependencies using pip, start the MCP service by running ‘python MCP_Servers/environment_server.py’, and initiate the LangGraph workflow testing with ‘python graphchat/main.py’.
Key features
Key features of AgriBrain_MCP include a multi-node dialogue workflow framework for agricultural tasks, a core server logic for task scheduling and model invocation, and standardized tool functions for various agricultural applications such as weather queries and crop data analysis.
Where to use
AgriBrain_MCP can be used in various fields related to agriculture, including pest management, crop monitoring, environmental sensing, and decision-making for agricultural machinery scheduling.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Agribrain Mcp
AgriBrain_MCP is an intelligent brain framework designed for smart agriculture, integrating various AI capabilities to enhance automation and intelligence in agricultural production through workflow orchestration, service deployment, and tool encapsulation.
Use cases
Use cases for AgriBrain_MCP include diagnosing pest issues through multi-turn interactions, providing real-time weather and environmental data, and assisting in crop growth monitoring and nutrient management.
How to use
To use AgriBrain_MCP, install the required dependencies using pip, start the MCP service by running ‘python MCP_Servers/environment_server.py’, and initiate the LangGraph workflow testing with ‘python graphchat/main.py’.
Key features
Key features of AgriBrain_MCP include a multi-node dialogue workflow framework for agricultural tasks, a core server logic for task scheduling and model invocation, and standardized tool functions for various agricultural applications such as weather queries and crop data analysis.
Where to use
AgriBrain_MCP can be used in various fields related to agriculture, including pest management, crop monitoring, environmental sensing, and decision-making for agricultural machinery scheduling.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
🌱 智慧农业大脑框架
本项目旨在构建一个面向智慧农业的智能大脑系统，整合多种 AI 能力，通过工作流编排、服务化部署与工具封装，提升农业生产的自动化与智能化水平。
📁 项目结构与模块说明
1. graphchat/ - LangGraph 工作流程图模块
该目录用于构建基于 LangGraph 的对话工作流框架，主要功能包括：
- 定义多节点对话流程（如感知 → 推理 → 决策）
- 管理节点状态和上下文传递
- 适用于农业生产中多轮交互任务场景（如病虫害诊断、田间问答）
2. mcp_servers/ - MCP 服务启动模块
该模块封装了智慧农业任务调度核心的服务端逻辑，包括：
- 启动 MCP（Multi-Component Process）服务器
- 负责模型调用、任务调度与服务注册
- 提供统一的 API 接口供前端与业务调用
3. tools/ - 工具节点模块
该目录下包含各种工具函数与原始 Function Call 形式工具，主要功能包括：
- 封装通用工具（如天气查询、作物数据分析、环境感知接口）
- 提供标准化的工具调用格式，支持 LangChain 工具集成
- 支持原始 OpenAI Function Calling 接口格式的工具定义
✅ TODO List
✅ 已完成项
- [x] 智慧农业大脑基础框架搭建
- [x] 环境监测助理模块
- [x] 病虫害管理助理模块
🚧 进行中 / 待完成项
- [ ] 作物生长监测子助理模块
- [ ] 农机调度决策子助理模块
- [ ] 水肥管理子助理模块
- [ ]
MCP_Servers模块功能完善 - [ ] 检索增强生成（RAG）能力集成
- [ ] RESTFUL风格后端接口更改
🚀 快速开始
# 安装依赖（建议使用 conda）
pip install -r requirements.txt
# 启动 MCP 服务
python MCP_Servers/environment_server.py
# 启动 LangGraph 流程测试
python graphchat/main.py
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
