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| # -*- coding: utf-8 -*- | |
| """FastMCP服务器实例""" | |
| from fastmcp import FastMCP | |
| from fastmcp.server.auth.providers.jwt import StaticTokenVerifier | |
| from app.services.mcp.tools import ask_grok_impl | |
| from app.core.config import setting | |
| def create_mcp_server() -> FastMCP: | |
| """创建MCP服务器实例，如果配置了API密钥则启用认证""" | |
| # 检查是否配置了API密钥 | |
| api_key = setting.grok_config.get("api_key") | |
| # 如果配置了API密钥，则启用静态token验证 | |
| auth = None | |
| if api_key: | |
| auth = StaticTokenVerifier( | |
| tokens={ | |
| api_key: { | |
| "client_id": "grok2api-client", | |
| "scopes": ["read", "write", "admin"] | |
| } | |
| }, | |
| required_scopes=["read"] | |
| ) | |
| # 创建FastMCP实例 | |
| return FastMCP( | |
| name="Grok2API-MCP", | |
| instructions="MCP server providing Grok AI chat capabilities. Use ask_grok tool to interact with Grok AI models.", | |
| auth=auth | |
| ) | |
| # 创建全局MCP实例 | |
| mcp = create_mcp_server() | |
| # 注册ask_grok工具 | |
| async def ask_grok( | |
| query: str, | |
| model: str = "grok-3-fast", | |
| system_prompt: str = None | |
| ) -> str: | |
| """ | |
| 调用Grok AI进行对话，尤其适用于当用户询问最新信息，需要调用搜索功能，或是想了解社交平台动态（如Twitter(X)、Reddit等）时。 | |
| Args: | |
| query: 用户的问题或指令 | |
| model: Grok模型名称,可选值: grok-3-fast(默认), grok-4-fast, grok-4-fast-expert, grok-4-expert, grok-4-heavy | |
| system_prompt: 可选的系统提示词,用于设定AI的角色或行为约束 | |
| Returns: | |
| Grok AI的完整回复内容,可能包括文本和图片链接(Markdown格式) | |
| Examples: | |
| - 简单问答: ask_grok("什么是Python?") | |
| - 指定模型: ask_grok("解释量子计算", model="grok-4-fast") | |
| - 带系统提示: ask_grok("写一首诗", system_prompt="你是一位古典诗人") | |
| """ | |
| return await ask_grok_impl(query, model, system_prompt) | |