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    Mcp Agent Forge

    A powerful MCP tool for forging and managing AI agent personalities with customizable expert traits and behaviors.

    6 stars
    Go
    Updated Sep 8, 2025

    Table of Contents

    • 中文版
    • 功能特点
    • 系统要求
    • 安装
    • MCP 配置
    • 配置说明
    • Configuration
    • Environment Variables
    • 使用方法
    • 示例
    • 基本用法
    • 实际应用案例
    • 贡献指南
    • 许可证
    • English Version
    • Features
    • System Requirements
    • Installation
    • MCP Configuration
    • Configuration Guide
    • Configuration
    • Environment Variables
    • Usage
    • Examples
    • Basic Usage
    • Real Application Case
    • Contributing
    • License

    Table of Contents

    • 中文版
    • 功能特点
    • 系统要求
    • 安装
    • MCP 配置
    • 配置说明
    • Configuration
    • Environment Variables
    • 使用方法
    • 示例
    • 基本用法
    • 实际应用案例
    • 贡献指南
    • 许可证
    • English Version
    • Features
    • System Requirements
    • Installation
    • MCP Configuration
    • Configuration Guide
    • Configuration
    • Environment Variables
    • Usage
    • Examples
    • Basic Usage
    • Real Application Case
    • Contributing
    • License

    Documentation

    Agent Forge - 智能体锻造工具 (AI Agent Forge Tool)

    English | 中文

    中文版

    Agent Forge 是一个智能体创建和管理平台,能够创建和管理具有特定性格特征的智能体,并模拟它们对问题的回答。通过Agent Forge MCP,你可以快速构建起一个类似于CO-STORM的多智能体协作研究项目。

    功能特点

    • 智能体锻造:创建具有特定性格特征的智能体
    • 思维模拟:模拟智能体回答问题
    • 完整管理:支持智能体的查询、列表、删除等操作
    • 多轮对话:支持深度的多轮对话交互
    • 自然语言处理:基于 DeepSeek API 的高级语言理解能力

    系统要求

    • Go 1.24.1 或更高版本
    • DeepSeek API 密钥

    安装

    bash
    git clone https://github.com/HundunOnline/mcp-agent-forge.git
    cd mcp-agent-forge && make build

    MCP 配置

    json
    {
      "mcpServers": {
        "mcp-agent-forge": {
          "command": "/path/to/mcp-agent-forge",
          "env": {
            "DEEPSEEK_API_KEY": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
          }
        }
      }
    }

    配置说明

    Configuration

    Environment Variables

    变量名描述默认值是否必需
    DEEPSEEK_API_KEYDeepSeek API 密钥-是
    LOG_LEVEL日志级别 (debug, info, warn, error)info否
    LOG_PATH日志文件路径./logs否
    CONFIG_PATH配置文件路径./config/config.yaml否
    PORT服务端口号8080否
    DEBUG调试模式开关false否

    使用方法

    • expert_personality_generation: 创建新的智能体
    • agent_answer: 模拟智能体回答问题
    • get_agent: 获取智能体信息
    • list_agents: 列出所有智能体
    • delete_agent: 删除智能体

    示例

    基本用法

    go
    // 创建智能体
    {
        "name": "expert_personality_generation",
        "arguments": {
            "agent_name": "马斯克思维模型",
            "core_traits": "系统思维,第一性原理,工程思维,风险管理,创新思维"
        }
    }
    
    // 智能体回答
    {
        "name": "agent_answer",
        "arguments": {
            "agent_id": "your_agent_id",
            "context": "如何看待特斯拉的发展策略?",
            "planned_rounds": 3,
            "current_round": 1,
            "need_more_rounds": false
        }
    }

    实际应用案例

    我们在 Claude AI 中创建了一个示例应用,展示了如何使用 Agent Forge 创建和管理专家智能体:

    Claude AI Demo

    这个示例展示了:

    • 如何创建具有特定专业背景的智能体
    • 如何进行多轮对话交互
    • 如何利用智能体的专业知识解决问题
    • 如何管理和调整智能体的行为

    贡献指南

    欢迎提交 Pull Request 或创建 Issue 来帮助改进这个项目。我们特别欢迎以下方面的贡献:

    • 新的智能体模型和特征
    • 性能优化
    • 文档改进
    • Bug 修复
    • 新功能建议

    许可证

    本项目采用 MIT 许可证。详见 LICENSE 文件。

    ---

    English Version

    Agent Forge is a platform for creating and managing AI agents with specific personality traits and simulating their responses to questions. Through agent forge mcp, you can quickly build a multi-agent collaboration research project similar to CO-STORM.

    Features

    • Agent Forging: Create agents with specific personality traits
    • Thought Simulation: Simulate agent responses to questions
    • Complete Management: Support for agent querying, listing, deletion, and other operations
    • Multi-round Dialogue: Support for deep multi-round conversation interactions
    • Natural Language Processing: Advanced language understanding capabilities based on DeepSeek API

    System Requirements

    • Go 1.24.1 or higher
    • DeepSeek API key

    Installation

    bash
    git clone https://github.com/HundunOnline/mcp-agent-forge.git
    cd agent-forge && make build

    MCP Configuration

    json
    {
      "mcpServers": {
        "mcp-agent-forge": {
          "command": "/path/to/mcp-agent-forge",
          "env": {
            "DEEPSEEK_API_KEY": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx",
          }
        }
      }
    }

    Configuration Guide

    Configuration

    Environment Variables

    Variable NameDescriptionDefault ValueRequired
    DEEPSEEK_API_KEYDeepSeek API Key-Yes
    LOG_LEVELLogging level (debug, info, warn, error)infoNo
    LOG_PATHLog file path./logsNo
    CONFIG_PATHConfiguration file path./config/config.yamlNo
    PORTService port8080No
    DEBUGDebug mode switchfalseNo

    Usage

    • expert_personality_generation: Create a new agent
    • agent_answer: Simulate agent responses
    • get_agent: Get agent information
    • list_agents: List all agents
    • delete_agent: Delete an agent

    Examples

    Basic Usage

    go
    // Create an agent
    {
        "name": "expert_personality_generation",
        "arguments": {
            "agent_name": "Elon Musk Thinking Model",
            "core_traits": "Systems Thinking,First Principles,Engineering Mindset,Risk Management,Innovation"
        }
    }
    
    // Agent response
    {
        "name": "agent_answer",
        "arguments": {
            "agent_id": "your_agent_id",
            "context": "What's your view on Tesla's development strategy?",
            "planned_rounds": 3,
            "current_round": 1,
            "need_more_rounds": false
        }
    }

    Real Application Case

    We created a sample application in Claude AI that demonstrates how to use Agent Forge to create and manage expert agents:

    Claude AI Demo

    This example shows:

    • How to create agents with specific professional backgrounds
    • How to conduct multi-round dialogue interactions
    • How to utilize agents' expertise to solve problems
    • How to manage and adjust agent behavior

    Contributing

    We welcome Pull Requests or Issues to help improve this project. We especially welcome contributions in the following areas:

    • New agent models and traits
    • Performance optimizations
    • Documentation improvements
    • Bug fixes
    • New feature suggestions

    License

    This project is licensed under the MIT License. See the LICENSE file for details.

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