MCP (Model Context Protocol) 深度解析
Model Context Protocol (MCP) 是 ByteBuddy 用于标准化 AI 模型交互的协议,提供统一的接口来访问各种 AI 服务和功能。
MCP 概述
协议目标
MCP 旨在实现:
- 标准化接口: 统一的 API 调用方式
- 提供商无关: 支持多个 AI 提供商
- 功能扩展: 易于添加新功能
- 兼容性: 向后兼容性保证
核心概念
- 提供商 (Provider): AI 服务提供商
- 模型 (Model): 具体的 AI 模型
- 角色 (Role): 模型的使用场景
- 能力 (Capability): 模型支持的功能
基础配置
标准 MCP 配置
yaml
models:
- name: "mcp-chat-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
capabilities: ["tool_use"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2000配置说明
- name: 模型的唯一标识符
- provider: AI 服务提供商
- model: 具体模型名称
- apiKey: API 认证密钥
- roles: 模型支持的角色
- capabilities: 模型的特殊能力
角色系统
支持的角色
yaml
models:
# 聊天角色
- name: "chat-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2000
# 编辑角色
- name: "edit-model"
provider: "anthropic"
model: "claude-3-sonnet"
apiKey: "${ANTHROPIC_API_KEY}"
roles: ["edit"]
defaultCompletionOptions:
temperature: 0.3
maxTokens: 4000
# 自动补全角色
- name: "autocomplete-model"
provider: "together"
model: "codellama/CodeLlama-13b-Instruct-hf"
apiKey: "${TOGETHER_API_KEY}"
roles: ["autocomplete"]
defaultCompletionOptions:
temperature: 0.1
maxTokens: 256
# 应用角色
- name: "apply-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["apply"]
defaultCompletionOptions:
temperature: 0.5
maxTokens: 4096
# 嵌入角色
- name: "embed-model"
provider: "openai"
model: "text-embedding-3-large"
apiKey: "${OPENAI_API_KEY}"
roles: ["embed"]
# 重排序角色
- name: "rerank-model"
provider: "cohere"
model: "rerank-english-v3.0"
apiKey: "${COHERE_API_KEY}"
roles: ["rerank"]多角色配置
单个模型可以支持多个角色:
yaml
models:
- name: "versatile-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat", "edit", "apply"]
defaultCompletionOptions:
temperature: 0.6
maxTokens: 4000能力系统
工具使用能力
yaml
models:
- name: "tool-capable-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
capabilities: ["tool_use"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 4000工具使用包括:
- 函数调用: 调用外部函数
- API 集成: 访问外部 API
- 数据检索: 查询数据库
- 文件操作: 读写文件
图像输入能力
yaml
models:
- name: "vision-model"
provider: "openai"
model: "gpt-4-vision-preview"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
capabilities: ["image_input"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 4096下一步编辑能力
yaml
models:
- name: "next-edit-model"
provider: "anthropic"
model: "claude-3-sonnet"
apiKey: "${ANTHROPIC_API_KEY}"
roles: ["edit"]
capabilities: ["next_edit"]
defaultCompletionOptions:
temperature: 0.3
maxTokens: 4000请求选项
基础请求选项
yaml
models:
- name: "configured-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
requestOptions:
timeout: 60000 # 60 秒
maxRetries: 3
retryDelay: 1000 # 1 秒
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2000自定义请求头
yaml
models:
- name: "custom-headers-model"
provider: "openai-compatible"
model: "custom-model"
apiKey: "${API_KEY}"
apiBase: "https://api.example.com/v1"
requestOptions:
headers:
"X-Custom-Header": "value"
"User-Agent": "ByteBuddy/1.0"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2000完成选项
标准完成选项
yaml
models:
- name: "tuned-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7 # 创造性 (0-2)
maxTokens: 2000 # 最大 token 数
topP: 0.9 # 核采样
frequencyPenalty: 0.0 # 频率惩罚 (-2 to 2)
presencePenalty: 0.0 # 存在惩罚 (-2 to 2)高级完成选项
yaml
models:
- name: "advanced-model"
provider: "openai"
model: "gpt-4"
apiKey: "${OPENAI_API_KEY}"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 4000
topP: 0.95
topK: 50
frequencyPenalty: 0.1
presencePenalty: 0.1
stopSequences: ["\n\n", "###"]提供商特定配置
Azure OpenAI
yaml
models:
- name: "azure-model"
provider: "azure-openai"
model: "gpt-4"
apiKey: "${AZURE_OPENAI_API_KEY}"
apiBase: "${AZURE_OPENAI_API_BASE}"
env:
deploymentName: "gpt-4-deployment"
apiVersion: "2024-02-15-preview"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 4000AWS Bedrock
yaml
models:
- name: "bedrock-model"
provider: "bedrock"
model: "anthropic.claude-3-sonnet-20240229-v1:0"
env:
region: "us-east-1"
accessKeyId: "${AWS_ACCESS_KEY_ID}"
secretAccessKey: "${AWS_SECRET_ACCESS_KEY}"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 4096Google Vertex AI
yaml
models:
- name: "vertexai-model"
provider: "vertexai"
model: "gemini-pro"
env:
projectId: "${GOOGLE_CLOUD_PROJECT_ID}"
location: "us-central1"
credentials: "${GOOGLE_APPLICATION_CREDENTIALS}"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2048MCP 扩展
自定义提供商
yaml
models:
- name: "custom-provider"
provider: "openai-compatible"
model: "custom-model"
apiKey: "${CUSTOM_API_KEY}"
apiBase: "https://api.custom.com/v1"
roles: ["chat"]
defaultCompletionOptions:
temperature: 0.7
maxTokens: 2000插件系统
ByteBuddy 支持通过 MCP 集成插件:
- 工具插件: 添加新的工具功能
- 提供商插件: 支持新的 AI 提供商
- 能力插件: 扩展模型能力
- 中间件插件: 请求/响应处理
最佳实践
1. 模型选择
- 根据任务选择合适的模型
- 平衡性能和成本
- 考虑延迟要求
- 评估质量需求
2. 参数调优
- 从默认值开始
- 根据反馈调整
- 记录最佳配置
- 定期重新评估
3. 错误处理
- 配置适当的超时
- 实施重试机制
- 记录错误日志
- 提供降级方案
4. 安全性
- 使用环境变量存储密钥
- 限制 API 调用频率
- 监控使用情况
- 定期轮换密钥
故障排除
常见问题
配置无效
解决方案:
- 检查 YAML 语法
- 验证必需字段
- 确认环境变量设置
API 调用失败
解决方案:
- 验证 API 密钥
- 检查网络连接
- 确认模型名称正确
- 查看提供商状态
性能问题
解决方案:
- 优化 token 限制
- 调整超时设置
- 考虑使用更快的模型
- 实施缓存策略
环境变量配置
bash
# ~/.bashrc 或 ~/.zshrc
export OPENAI_API_KEY="your-openai-api-key"
export ANTHROPIC_API_KEY="your-anthropic-api-key"
export TOGETHER_API_KEY="your-together-api-key"
export COHERE_API_KEY="your-cohere-api-key"
# 云服务提供商
export AZURE_OPENAI_API_KEY="your-azure-key"
export AZURE_OPENAI_API_BASE="https://your-resource.openai.azure.com"
export AWS_ACCESS_KEY_ID="your-aws-access-key"
export AWS_SECRET_ACCESS_KEY="your-aws-secret-key"
export GOOGLE_CLOUD_PROJECT_ID="your-project-id"
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/credentials.json"通过理解和正确使用 MCP,您可以充分发挥 ByteBuddy 的强大功能,构建高效的 AI 辅助开发环境。