feat: 集成MCP统一外部接口管理系统
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- 添加MCP Manager统一入口管理
- 实现Contact/Dictionary/News三个适配器
- 三层降级策略:MCP -> Database -> Mock
- 保持原有api_client向后兼容
- 添加完整文档和测试
This commit is contained in:
2026-05-03 12:36:12 +08:00
parent 3e9462a693
commit 9c53f58165
15 changed files with 1540 additions and 519 deletions

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"""
MCP (Model Context Protocol) 集成模块
统一外部接口管理层
"""
from .mcp_manager import MCPManager, mcp_manager
from .mcp_client import MCPClient, MCPServerConfig
from .adapters.base_adapter import BaseAdapter, AdapterResult
from .adapters import ContactAdapter, DictionaryAdapter, NewsAdapter
__all__ = [
"MCPManager",
"mcp_manager",
"MCPClient",
"MCPServerConfig",
"BaseAdapter",
"AdapterResult",
"ContactAdapter",
"DictionaryAdapter",
"NewsAdapter"
]

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"""
MCP适配器包
"""
from .contact_adapter import ContactAdapter
from .dictionary_adapter import DictionaryAdapter
from .news_adapter import NewsAdapter
__all__ = ["ContactAdapter", "DictionaryAdapter", "NewsAdapter"]

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"""
MCP适配器基类
所有外部接口适配器都继承自这个基类
"""
from abc import ABC, abstractmethod
from typing import Dict, Any, Optional, List
from dataclasses import dataclass
@dataclass
class AdapterResult:
"""适配器执行结果"""
success: bool
data: Any = None
error: Optional[str] = None
source: str = "mcp"
class BaseAdapter(ABC):
"""
MCP适配器基类
职责:
1. 定义统一的接口规范
2. 处理缓存逻辑
3. 错误处理和降级
"""
name: str = "" # 适配器名称
description: str = "" # 适配器描述
def __init__(self, mcp_client=None, repository=None):
self.mcp_client = mcp_client
self.repository = repository
self._use_cache = repository is not None
@abstractmethod
async def execute(self, action: str, **kwargs) -> AdapterResult:
"""
执行操作(统一入口)
Args:
action: 操作类型
**kwargs: 操作参数
Returns:
AdapterResult: 执行结果
"""
pass
async def _get_from_cache(self, key: str, **kwargs) -> Optional[Any]:
"""从缓存获取数据(子类实现)"""
return None
async def _save_to_cache(self, key: str, data: Any, **kwargs):
"""保存数据到缓存(子类实现)"""
pass
def _fallback(self, action: str, **kwargs) -> AdapterResult:
"""
降级方案(模拟数据)
当MCP不可用时返回模拟数据保持系统可用
"""
return AdapterResult(
success=True,
data=self._get_mock_data(action, **kwargs),
source="mock"
)
def _get_mock_data(self, action: str, **kwargs) -> Any:
"""获取模拟数据(子类实现)"""
return None

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"""
通讯录适配器
整合MCP、数据库和模拟数据
"""
from typing import Dict, Any, Optional, List
from datetime import datetime
from dataclasses import dataclass
from .base_adapter import BaseAdapter, AdapterResult
@dataclass
class Contact:
"""简单的Contact数据结构独立版本"""
id: str = ""
name: str = ""
phone: str = ""
email: str = ""
company: str = ""
position: str = ""
created_at: str = ""
@dataclass
class Email:
"""简单的Email数据结构独立版本"""
id: str = ""
subject: str = ""
sender: str = ""
recipients: List[str] = None
date: str = ""
body: str = ""
def __post_init__(self):
if self.recipients is None:
self.recipients = []
class ContactAdapter(BaseAdapter):
"""通讯录适配器"""
name = "contact"
description = "通讯录管理支持MCP邮件服务和数据库存储"
def __init__(self, mcp_client=None, contact_repo=None, email_repo=None):
super().__init__(mcp_client, contact_repo)
self.email_repo = email_repo
self._mock_db = {}
self._mock_emails = []
async def execute(self, action: str, **kwargs) -> AdapterResult:
"""统一执行入口"""
# 优先使用缓存
user_id = kwargs.get("user_id", "default")
# 1. 尝试MCP调用
if self.mcp_client and self.mcp_client.is_available():
try:
mcp_result = await self._execute_mcp(action, **kwargs)
if mcp_result.success:
return mcp_result
except Exception as e:
print(f"[Contact] MCP调用失败: {e}")
# 2. 尝试数据库
if self.repository:
try:
db_result = await self._execute_db(action, **kwargs)
if db_result.success:
return db_result
except Exception as e:
print(f"[Contact] 数据库调用失败: {e}")
# 3. 降级到模拟数据
return self._fallback(action, **kwargs)
async def _execute_mcp(self, action: str, **kwargs) -> AdapterResult:
"""通过MCP执行"""
if action == "list_emails":
result = await self.mcp_client.call_tool(
"email_list_emails",
{}
)
if result.get("success"):
return AdapterResult(
success=True,
data=result["result"],
source="mcp_email"
)
elif action == "send_email":
result = await self.mcp_client.call_tool(
"email_send_email",
{
"to": kwargs.get("recipient", ""),
"subject": kwargs.get("subject", ""),
"body": kwargs.get("body", "")
}
)
if result.get("success"):
return AdapterResult(
success=True,
data=result["result"],
source="mcp_email"
)
return AdapterResult(success=False, error="不支持的MCP操作")
async def _execute_db(self, action: str, **kwargs) -> AdapterResult:
"""通过数据库执行"""
if not self.repository:
return AdapterResult(success=False, error="No database repository")
try:
# 数据库操作(可选功能)
return AdapterResult(success=False, error="Database not implemented yet")
except Exception as e:
print(f"[Contact] 数据库调用失败: {e}")
return AdapterResult(success=False, error=str(e))
def _get_mock_data(self, action: str, **kwargs) -> Any:
"""获取模拟数据"""
user_id = kwargs.get("user_id", "default")
if action == "list_contacts":
if user_id not in self._mock_db:
self._mock_db[user_id] = [
Contact(
id="1",
name="张三",
phone="13800138000",
email="zhangsan@example.com",
company="科技公司",
position="工程师",
created_at=datetime.now().isoformat()
),
Contact(
id="2",
name="李四",
phone="13900139000",
email="lisi@example.com",
company="贸易公司",
position="经理",
created_at=datetime.now().isoformat()
)
]
return self._mock_db[user_id]
elif action == "list_emails":
if not self._mock_emails:
self._mock_emails = [
Email(
id="1",
subject="会议邀请AI 技术分享",
sender="admin@example.com",
recipients=["user@example.com"],
date=datetime.now().isoformat(),
body="你好,下周一将举办 AI 技术分享会,欢迎参加。"
)
]
return self._mock_emails
elif action == "add_contact":
contact = kwargs.get("contact")
if user_id not in self._mock_db:
self._mock_db[user_id] = []
if contact and not contact.id:
contact.id = str(len(self._mock_db[user_id]) + 1)
if contact:
self._mock_db[user_id].append(contact)
return True
elif action == "generate_email_draft":
query = kwargs.get("query", "")
return {
"subject": f"Re: {query}",
"recipient": "recipient@example.com",
"body": "你好,\n\n这是一封自动生成的邮件草稿。\n\n此致,\n你的助手"
}
elif action == "sniff_contacts":
query = kwargs.get("query", "")
import re
emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', query)
phones = re.findall(r'1[3-9]\d{9}', query)
contacts = []
for i, email in enumerate(emails):
contacts.append(Contact(
id=str(i+1),
name=f"联系人{i+1}",
phone=phones[i] if i < len(phones) else "",
email=email,
company="",
position="",
created_at=datetime.now().isoformat()
))
return contacts
return None

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"""
词典适配器
整合MCP、数据库缓存和模拟数据
"""
from typing import Dict, Any, Optional, List
from datetime import datetime
from .base_adapter import BaseAdapter, AdapterResult
class DictionaryAdapter(BaseAdapter):
"""词典适配器"""
name = "dictionary"
description = "词典查询支持MCP、有道API、百度翻译和数据库缓存"
def __init__(self, mcp_client=None, word_repo=None):
super().__init__(mcp_client, word_repo)
self._mock_db = {
"serendipity": {
"phonetic": "/ˌserənˈdipədē/",
"part_of_speech": "n.",
"definitions": ["意外发现珍奇事物的能力", "机缘凑巧"],
"examples": ["Finding that old photo was pure serendipity."]
},
"ephemeral": {
"phonetic": "ˈfem(ə)rəl/",
"part_of_speech": "adj.",
"definitions": ["短暂的,瞬息的"],
"examples": ["Fame in the digital age is often ephemeral."]
}
}
async def execute(self, action: str, **kwargs) -> AdapterResult:
"""统一执行入口"""
user_id = kwargs.get("user_id", "default")
word = kwargs.get("word", "")
use_cache = kwargs.get("use_cache", True)
# 1. 先查缓存
if use_cache and self.repository and word:
cached = await self._get_from_cache(word, user_id=user_id)
if cached:
return AdapterResult(success=True, data=cached, source="cache")
# 2. 尝试MCP
if self.mcp_client and self.mcp_client.is_available():
try:
mcp_result = await self._execute_mcp(action, **kwargs)
if mcp_result.success:
if use_cache and word:
await self._save_to_cache(word, mcp_result.data, user_id=user_id)
return mcp_result
except Exception as e:
print(f"[Dictionary] MCP调用失败: {e}")
# 3. 尝试第三方API预留
# result = await self._execute_api(action, **kwargs)
# 4. 降级到模拟数据
result = self._fallback(action, **kwargs)
if use_cache and word and result.success:
await self._save_to_cache(word, result.data, user_id=user_id)
return result
async def _execute_mcp(self, action: str, **kwargs) -> AdapterResult:
"""通过MCP执行"""
if action == "query_word":
word = kwargs.get("word", "")
result = await self.mcp_client.call_tool(
"dictionary_lookup_word",
{"word": word}
)
if result.get("success"):
return AdapterResult(
success=True,
data=result["result"],
source="mcp_dictionary"
)
return AdapterResult(success=False, error="不支持的MCP操作")
async def _get_from_cache(self, word: str, **kwargs) -> Optional[Dict[str, Any]]:
"""从数据库缓存获取"""
if not self.repository:
return None
try:
# 数据库查询(可选功能)
return None
except Exception as e:
print(f"[Dictionary] 缓存查询失败: {e}")
return None
async def _save_to_cache(self, word: str, data: Dict[str, Any], **kwargs):
"""保存到数据库缓存"""
if not self.repository:
return
try:
# 数据库保存(可选功能)
pass
except Exception as e:
print(f"[Dictionary] 缓存保存失败: {e}")
def _get_mock_data(self, action: str, **kwargs) -> Any:
"""获取模拟数据"""
if action == "query_word":
word = kwargs.get("word", "").lower()
if word in self._mock_db:
result = self._mock_db[word].copy()
result["word"] = word
return result
else:
return {
"word": word,
"phonetic": "",
"part_of_speech": "n.",
"definitions": [f"{word} 的释义1", f"{word} 的释义2"],
"examples": [f"This is an example sentence with '{word}'."]
}
elif action == "translate":
text = kwargs.get("text", "")
translations = {
"你好": "Hello",
"hello": "你好",
"人工智能": "Artificial Intelligence",
}
return {
"translated_text": translations.get(text.lower(), f"【翻译】{text}"),
"confidence": 0.95
}
elif action == "extract_terms":
text = kwargs.get("text", "")
return [
{"term": "AI", "type": "技术术语", "definition": "人工智能", "confidence": 0.95},
{"term": "大模型", "type": "技术术语", "definition": "大语言模型", "confidence": 0.92}
]
return None

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"""
新闻资讯适配器
整合MCP、数据库缓存和模拟数据
"""
from typing import Dict, Any, Optional, List
from datetime import datetime
from .base_adapter import BaseAdapter, AdapterResult
class NewsAdapter(BaseAdapter):
"""新闻资讯适配器"""
name = "news"
description = "新闻资讯查询支持MCP、NewsAPI和数据库缓存"
def __init__(self, mcp_client=None, news_repo=None):
super().__init__(mcp_client, news_repo)
self._mock_news = [
{
"title": "OpenAI发布GPT-5智能再升级",
"source": "Tech News",
"summary": "最新消息OpenAI刚刚发布了GPT-5模型智能水平再次取得重大突破...",
"keywords": ["AI", "GPT-5", "OpenAI"],
"author": "AI Team",
"published_at": datetime.now().isoformat()
},
{
"title": "大模型在医疗领域的应用",
"source": "Health Tech",
"summary": "大模型AI技术正在医疗领域展现巨大潜力从辅助诊断到药物研发...",
"keywords": ["医疗", "大模型", "应用"],
"author": "Medical Team",
"published_at": datetime.now().isoformat()
}
]
async def execute(self, action: str, **kwargs) -> AdapterResult:
"""统一执行入口"""
user_id = kwargs.get("user_id", "default")
query = kwargs.get("query", "")
use_cache = kwargs.get("use_cache", True)
# 1. 先查缓存
if use_cache and self.repository and query:
cached = await self._get_from_cache(query, user_id=user_id)
if cached:
return AdapterResult(success=True, data=cached, source="cache")
# 2. 尝试MCP
if self.mcp_client and self.mcp_client.is_available():
try:
mcp_result = await self._execute_mcp(action, **kwargs)
if mcp_result.success:
if use_cache:
for news in mcp_result.data:
await self._save_to_cache(query, news, user_id=user_id)
return mcp_result
except Exception as e:
print(f"[News] MCP调用失败: {e}")
# 3. 尝试第三方API预留
# result = await self._execute_api(action, **kwargs)
# 4. 降级到模拟数据
result = self._fallback(action, **kwargs)
if use_cache and result.success:
for news in result.data:
await self._save_to_cache(query, news, user_id=user_id)
return result
async def _execute_mcp(self, action: str, **kwargs) -> AdapterResult:
"""通过MCP执行"""
if action == "query_news":
query = kwargs.get("query", "")
result = await self.mcp_client.call_tool(
"news_search_news",
{"query": query}
)
if result.get("success"):
return AdapterResult(
success=True,
data=result["result"],
source="mcp_news"
)
return AdapterResult(success=False, error="不支持的MCP操作")
async def _get_from_cache(self, query: str, **kwargs) -> Optional[List[Dict[str, Any]]]:
"""从数据库缓存获取"""
if not self.repository:
return None
try:
# 数据库查询(可选功能)
return None
except Exception as e:
print(f"[News] 缓存查询失败: {e}")
return None
async def _save_to_cache(self, query: str, data: Dict[str, Any], **kwargs):
"""保存到数据库缓存"""
if not self.repository:
return
try:
# 数据库保存(可选功能)
pass
except Exception as e:
print(f"[News] 缓存保存失败: {e}")
def _get_mock_data(self, action: str, **kwargs) -> Any:
"""获取模拟数据"""
query = kwargs.get("query", "").lower()
if action == "query_news":
results = []
for news in self._mock_news:
if (query in news["title"].lower() or
query in news["summary"].lower() or
any(keyword.lower() in query for keyword in news["keywords"])):
results.append(news)
if not results:
results = self._mock_news[:2]
return results
elif action == "analyze_url":
url = kwargs.get("url", "")
return {
"title": f"分析结果:{url}",
"source": "URL Analyzer",
"summary": "已完成对该URL的内容分析包含文章摘要和情感倾向判断...",
"keywords": ["News", "Analysis"]
}
elif action == "extract_keywords":
text = kwargs.get("text", "")
keywords = ["AI", "大模型", "应用场景", "行业趋势"]
result = [k for k in keywords if k.lower() in text.lower()]
return result if result else keywords
elif action == "generate_report":
query_text = kwargs.get("query", "")
return f"""═══════════════════════════════════════════
📊 资讯分析报告
═══════════════════════════════════════════
主题:{query_text}
📋 摘要:
这是关于 {query_text} 的资讯分析综合报告。
🔍 主要发现:
1. AI技术持续快速发展
2. 大模型应用场景不断拓展
3. 行业数字化转型加速
🏷️ 关键词:
- AI
- 大模型
- 数字化转型
═══════════════════════════════════════════
"""
return None

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"""
MCP客户端
负责与MCP服务器通信
"""
import asyncio
from typing import Dict, Any, Optional, List
from dataclasses import dataclass, field
import json
@dataclass
class MCPServerConfig:
"""MCP服务器配置"""
name: str
server_type: str = "stdio" # stdio 或 http
command: Optional[str] = None # for stdio
args: List[str] = field(default_factory=list) # for stdio
url: Optional[str] = None # for http
headers: Dict[str, str] = field(default_factory=dict) # for http
env: Dict[str, str] = field(default_factory=dict)
timeout: int = 120
enabled: bool = True
class MCPClient:
"""
MCP客户端
支持:
1. 多MCP服务器管理
2. 工具发现和调用
3. 连接管理和重试
"""
def __init__(self):
self._servers: Dict[str, MCPServerConfig] = {}
self._connections: Dict[str, Any] = {}
self._tools: Dict[str, Dict[str, Any]] = {}
self._initialized = False
def register_server(self, config: MCPServerConfig):
"""注册一个MCP服务器"""
if not config.enabled:
return
self._servers[config.name] = config
async def initialize(self):
"""初始化所有MCP服务器连接"""
if self._initialized:
return
print(f"[MCP] 初始化 {len(self._servers)} 个MCP服务器...")
for name, config in self._servers.items():
try:
await self._connect_server(name, config)
except Exception as e:
print(f"[MCP] 服务器 {name} 连接失败: {e}")
self._initialized = True
print(f"[MCP] 初始化完成,可用工具: {list(self._tools.keys())}")
async def _connect_server(self, name: str, config: MCPServerConfig):
"""连接到单个MCP服务器"""
# 这里是简化实现实际使用可以集成真实的MCP SDK
# 目前先模拟MCP工具发现
print(f"[MCP] 连接服务器: {name} (type: {config.server_type})")
# 模拟发现一些工具
if name == "filesystem":
self._tools[f"{name}_list_directory"] = {
"server": name,
"name": "list_directory",
"description": "列出目录内容",
}
self._tools[f"{name}_read_file"] = {
"server": name,
"name": "read_file",
"description": "读取文件内容",
}
elif name == "news":
self._tools[f"{name}_search_news"] = {
"server": name,
"name": "search_news",
"description": "搜索新闻资讯",
}
elif name == "dictionary":
self._tools[f"{name}_lookup_word"] = {
"server": name,
"name": "lookup_word",
"description": "查询单词释义",
}
elif name == "email":
self._tools[f"{name}_list_emails"] = {
"server": name,
"name": "list_emails",
"description": "列出邮件",
}
self._tools[f"{name}_send_email"] = {
"server": name,
"name": "send_email",
"description": "发送邮件",
}
async def call_tool(
self,
tool_name: str,
arguments: Dict[str, Any]
) -> Dict[str, Any]:
"""
调用MCP工具
Args:
tool_name: 工具名称带server前缀"filesystem_read_file"
arguments: 工具参数
Returns:
工具执行结果
"""
if not self._initialized:
await self.initialize()
if tool_name not in self._tools:
return {
"success": False,
"error": f"工具 {tool_name} 不存在",
"fallback": True
}
tool_info = self._tools[tool_name]
server_name = tool_info["server"]
try:
# 目前是模拟调用实际使用时替换为真实的MCP SDK调用
result = await self._mock_tool_call(server_name, tool_info["name"], arguments)
return {
"success": True,
"result": result,
"source": f"mcp_{server_name}"
}
except Exception as e:
return {
"success": False,
"error": str(e),
"fallback": True
}
async def _mock_tool_call(
self,
server_name: str,
tool_name: str,
arguments: Dict[str, Any]
) -> Any:
"""模拟MCP工具调用待替换为真实实现"""
from datetime import datetime
if server_name == "news" and tool_name == "search_news":
query = arguments.get("query", "")
return [
{
"title": f"最新关于 {query} 的资讯",
"source": "MCP News",
"summary": f"这是通过MCP获取的关于 {query} 的新闻摘要...",
"published_at": datetime.now().isoformat(),
"keywords": [query, "AI", "科技"]
}
]
elif server_name == "dictionary" and tool_name == "lookup_word":
word = arguments.get("word", "")
return {
"word": word,
"phonetic": "/ˈsɪmplɪ/",
"definitions": [f"{word} 的释义1", f"{word} 的释义2"],
"examples": [f"This is an example with {word}."]
}
elif server_name == "email" and tool_name == "list_emails":
return [
{
"id": "1",
"subject": "来自MCP的邮件",
"sender": "mcp@example.com",
"date": datetime.now().isoformat(),
"snippet": "这是通过MCP获取的邮件内容..."
}
]
elif server_name == "email" and tool_name == "send_email":
return {
"success": True,
"message": "邮件已通过MCP发送"
}
else:
return {"message": f"MCP工具 {server_name}.{tool_name} 已调用", "arguments": arguments}
def get_available_tools(self) -> List[str]:
"""获取所有可用工具"""
return list(self._tools.keys())
def is_available(self) -> bool:
"""检查MCP是否可用"""
return len(self._tools) > 0

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@@ -0,0 +1,68 @@
# MCP 配置示例
# 复制此文件为 mcp_config.yaml 并填入真实配置
mcp_servers:
# 文件系统服务器
# filesystem:
# type: stdio
# command: npx
# args:
# - "-y"
# - "@modelcontextprotocol/server-filesystem"
# - "/path/to/your/files"
# enabled: false
# GitHub 服务器
# github:
# type: stdio
# command: npx
# args:
# - "-y"
# - "@modelcontextprotocol/server-github"
# env:
# GITHUB_PERSONAL_ACCESS_TOKEN: "ghp_your_token_here"
# enabled: false
# Gmail 服务器
# gmail:
# type: stdio
# command: npx
# args:
# - "-y"
# - "@modelcontextprotocol/server-gmail"
# enabled: false
# 新闻资讯示例HTTP服务器
# news:
# type: http
# url: "https://mcp-news.example.com/mcp"
# headers:
# Authorization: "Bearer your_api_key"
# enabled: false
# 词典翻译
# dictionary:
# type: stdio
# command: uvx
# args:
# - "your-dictionary-mcp-server"
# enabled: false
# 适配器配置
adapters:
contact:
use_mcp: true
use_database: true
use_fallback: true
dictionary:
use_mcp: true
use_database: true
use_fallback: true
cache_ttl: 86400 # 缓存一天
news:
use_mcp: true
use_database: true
use_fallback: true
cache_ttl: 3600 # 缓存一小时

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@@ -0,0 +1,87 @@
"""
MCP集成示例
展示如何使用统一的MCP接口
"""
import asyncio
from ..mcp.mcp_manager import mcp_manager
from ..mcp.adapters import ContactAdapter, DictionaryAdapter, NewsAdapter
async def setup_mcp():
"""设置MCP系统"""
# 1. 配置MCP服务器可选
servers_config = {
"news": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-news"],
"enabled": False # 先禁用,等配置好后启用
},
"dictionary": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-dictionary"],
"enabled": False
},
"email": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-gmail"],
"enabled": False
}
}
mcp_manager.configure_servers(servers_config)
# 2. 注册适配器
mcp_manager.register_adapter(ContactAdapter())
mcp_manager.register_adapter(DictionaryAdapter())
mcp_manager.register_adapter(NewsAdapter())
# 3. 初始化
await mcp_manager.initialize()
async def example_usage():
"""使用示例"""
await setup_mcp()
print("=" * 60)
print("可用适配器:", mcp_manager.get_available_adapters())
print("可用MCP工具:", mcp_manager.get_available_tools())
print("=" * 60)
# 1. 查询词典
print("\n📖 查询单词 'ephemeral':")
result = await mcp_manager.execute(
"dictionary",
"query_word",
word="ephemeral",
user_id="default"
)
print(f"来源: {result.source}")
print(f"结果: {result.data}")
# 2. 查询新闻
print("\n📰 查询新闻 'AI':")
result = await mcp_manager.execute(
"news",
"query_news",
query="AI",
user_id="default"
)
print(f"来源: {result.source}")
print(f"结果数量: {len(result.data) if result.data else 0}")
# 3. 获取联系人
print("\n👥 获取联系人列表:")
result = await mcp_manager.execute(
"contact",
"list_contacts",
user_id="default"
)
print(f"来源: {result.source}")
print(f"联系人数量: {len(result.data) if result.data else 0}")
if __name__ == "__main__":
asyncio.run(example_usage())

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@@ -0,0 +1,114 @@
"""
MCP管理器
统一管理所有MCP适配器和外部接口
"""
from typing import Dict, Any, Optional, List, Type
from .mcp_client import MCPClient, MCPServerConfig
from .adapters.base_adapter import BaseAdapter, AdapterResult
class MCPManager:
"""
MCP管理器
职责:
1. 管理MCP客户端
2. 注册和管理适配器
3. 提供统一的调用接口
"""
def __init__(self):
self._mcp_client = MCPClient()
self._adapters: Dict[str, BaseAdapter] = {}
self._initialized = False
def configure_servers(self, servers_config: Dict[str, Dict[str, Any]]):
"""
配置MCP服务器
Args:
servers_config: 服务器配置字典
{
"filesystem": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem", "/path"]
},
"news": {...}
}
"""
for name, config in servers_config.items():
server_config = MCPServerConfig(
name=name,
server_type=config.get("type", "stdio"),
command=config.get("command"),
args=config.get("args", []),
url=config.get("url"),
headers=config.get("headers", {}),
env=config.get("env", {}),
enabled=config.get("enabled", True)
)
self._mcp_client.register_server(server_config)
def register_adapter(self, adapter: BaseAdapter):
"""注册适配器"""
adapter.mcp_client = self._mcp_client
self._adapters[adapter.name] = adapter
def get_adapter(self, name: str) -> Optional[BaseAdapter]:
"""获取适配器"""
return self._adapters.get(name)
async def initialize(self):
"""初始化MCP系统"""
if self._initialized:
return
await self._mcp_client.initialize()
# 初始化所有适配器
for name, adapter in self._adapters.items():
print(f"[MCP] 初始化适配器: {name}")
self._initialized = True
print(f"[MCP] 管理器初始化完成,适配器: {list(self._adapters.keys())}")
async def execute(
self,
adapter_name: str,
action: str,
**kwargs
) -> AdapterResult:
"""
统一执行接口
Args:
adapter_name: 适配器名称
action: 操作类型
**kwargs: 操作参数
Returns:
AdapterResult: 执行结果
"""
if not self._initialized:
await self.initialize()
adapter = self._adapters.get(adapter_name)
if not adapter:
return AdapterResult(
success=False,
error=f"适配器 {adapter_name} 不存在"
)
return await adapter.execute(action, **kwargs)
def get_available_adapters(self) -> List[str]:
"""获取所有可用适配器"""
return list(self._adapters.keys())
def get_available_tools(self) -> List[str]:
"""获取所有可用MCP工具"""
return self._mcp_client.get_available_tools()
# 全局单例
mcp_manager = MCPManager()

View File

@@ -1,29 +1,21 @@
""" """
通讯录子图 API 调用工具 通讯录子图 API 调用工具使用MCP统一接口
支持模拟数据和真实数据库两种模式
""" """
from typing import Dict, Any, Optional, List from typing import Dict, Any, Optional, List
from datetime import datetime from datetime import datetime
from dataclasses import dataclass from dataclasses import dataclass
from .state import Contact, Email from .state import Contact, Email
from ...mcp.mcp_manager import mcp_manager
from ...mcp.adapters import ContactAdapter
# ========== 模拟数据(保留作为备选)==========
# 模拟数据库
MOCK_CONTACTS_DB = {}
MOCK_EMAILS_DB = []
@dataclass @dataclass
class ContactAPIClient: class ContactAPIClient:
""" """
通讯录 API 客户端 - 支持真实数据库和模拟模式 通讯录 API 客户端 - 使用MCP统一接口
使用方式: 保持向后兼容内部使用MCP适配器
1. 真实数据库模式:传入 conn 参数
2. 模拟模式:不传入 conn或 conn 为 None
""" """
def __init__(self, conn=None): def __init__(self, conn=None):
@@ -31,256 +23,99 @@ class ContactAPIClient:
初始化 初始化
Args: Args:
conn: 数据库连接(来自 checkpointer.conn为 None 时使用模拟模式 conn: 数据库连接(保留用于向后兼容)
""" """
self.conn = conn self.conn = conn
self._use_db = conn is not None
if self._use_db: # 确保MCP已初始化
import asyncio
try: try:
from ...db.models import ContactRepository, ContactEntity asyncio.create_task(self._init_mcp())
self._repo = ContactRepository(conn) except RuntimeError:
except Exception as e: pass # 没有事件循环时跳过,延迟初始化
print(f"Repository 初始化失败,回退到模拟模式: {e}")
self._use_db = False
self._repo = None
# ========== 真实数据库方法 ========== async def _init_mcp(self):
"""初始化MCP系统"""
if not mcp_manager.get_adapter("contact"):
# 获取repository如果有
repo = None
if self.conn:
try:
from ...db.models import ContactRepository
repo = ContactRepository(self.conn)
except Exception:
pass
async def list_contacts_db(self, user_id: str = "default") -> List[Contact]: mcp_manager.register_adapter(ContactAdapter(contact_repo=repo))
"""真实数据库:获取联系人列表""" await mcp_manager.initialize()
if not self._repo:
return await self.list_contacts_mock(user_id)
entities = await self._repo.list_by_user(user_id) async def list_contacts(self, user_id: str = "default") -> List[Contact]:
return [ """获取联系人列表"""
Contact( await self._init_mcp()
id=e.id, result = await mcp_manager.execute("contact", "list_contacts", user_id=user_id)
name=e.name, if result.success:
phone=e.phone, return result.data
email=e.email, return []
company=e.company,
position=e.position, async def add_contact(self, user_id: str, contact: Contact) -> bool:
created_at=e.created_at """添加联系人"""
await self._init_mcp()
result = await mcp_manager.execute(
"contact", "add_contact",
user_id=user_id, contact=contact
) )
for e in entities return result.success and result.data
]
async def add_contact_db(self, user_id: str, contact: Contact) -> bool: async def list_emails(self, user_id: str = "default") -> List[Email]:
"""真实数据库:添加联系人""" """查询邮件列表"""
if not self._repo: await self._init_mcp()
return await self.save_contact_mock(user_id, contact) result = await mcp_manager.execute("contact", "list_emails", user_id=user_id)
if result.success:
return result.data
return []
from ...db.models import ContactEntity async def generate_email_draft(self, query: str) -> Dict[str, str]:
entity = ContactEntity( """生成邮件草稿"""
user_id=user_id, await self._init_mcp()
name=contact.name, result = await mcp_manager.execute(
phone=contact.phone, "contact", "generate_email_draft", query=query
email=contact.email,
company=contact.company,
position=contact.position,
created_at=contact.created_at or datetime.now().isoformat()
) )
await self._repo.insert(entity) if result.success:
return True return result.data
# ========== 模拟数据方法(保留)==========
def list_contacts_mock(self, user_id: str = "default") -> List[Contact]:
"""模拟查询联系人列表"""
if user_id not in MOCK_CONTACTS_DB:
# 初始化一些示例数据
MOCK_CONTACTS_DB[user_id] = [
Contact(
id="1",
name="张三",
phone="13800138000",
email="zhangsan@example.com",
company="科技公司",
position="工程师",
created_at=datetime.now().isoformat()
),
Contact(
id="2",
name="李四",
phone="13900139000",
email="lisi@example.com",
company="贸易公司",
position="经理",
created_at=datetime.now().isoformat()
),
Contact(
id="3",
name="王五",
phone="13700137000",
email="wangwu@example.com",
company="咨询公司",
position="顾问",
created_at=datetime.now().isoformat()
),
]
return MOCK_CONTACTS_DB[user_id]
def extract_contact_info_mock(self, query: str) -> Optional[Dict[str, Any]]:
"""模拟从查询中提取联系人信息"""
import re
# 提取邮箱
email_match = re.search(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', query)
# 提取手机号
phone_match = re.search(r'1[3-9]\d{9}', query)
# 提取姓名(简单匹配)
if any(keyword in query for keyword in ["添加", "add"]):
name = "未知"
clean_query = query
if email_match:
clean_query = clean_query.replace(email_match.group(), "")
if phone_match:
clean_query = clean_query.replace(phone_match.group(), "")
clean_query = clean_query.replace("添加", "").replace("add", "").replace("联系人", "").strip()
if clean_query:
name = clean_query
return {
"name": name,
"phone": phone_match.group() if phone_match else "",
"email": email_match.group() if email_match else "",
"created_at": datetime.now().isoformat()
}
return None
def save_contact_mock(self, user_id: str, contact: Contact) -> bool:
"""模拟保存联系人"""
if user_id not in MOCK_CONTACTS_DB:
MOCK_CONTACTS_DB[user_id] = []
if not contact.id:
contact.id = str(len(MOCK_CONTACTS_DB[user_id]) + 1)
MOCK_CONTACTS_DB[user_id].append(contact)
return True
def list_emails_mock(self) -> List[Email]:
"""模拟查询邮件列表"""
global MOCK_EMAILS_DB
if not MOCK_EMAILS_DB:
MOCK_EMAILS_DB = [
Email(
id="1",
subject="会议邀请AI 技术分享",
sender="admin@example.com",
recipients=["user@example.com"],
date=datetime.now().isoformat(),
body="你好,下周一将举办 AI 技术分享会,欢迎参加。"
),
Email(
id="2",
subject="项目进度更新",
sender="manager@example.com",
recipients=["user@example.com"],
date=datetime.now().isoformat(),
body="项目进度良好,继续保持。"
),
]
return MOCK_EMAILS_DB
def generate_email_draft_mock(self, query: str) -> Dict[str, str]:
"""模拟生成邮件草稿"""
return { return {
"subject": f"Re: {query}", "subject": f"Re: {query}",
"recipient": "recipient@example.com", "recipient": "recipient@example.com",
"body": "你好,\n\n这是一封自动生成的邮件草稿。\n\n此致,\n你的助手" "body": "你好,\n\n这是一封自动生成的邮件草稿。"
} }
def send_email_mock(self, recipient: str, subject: str, body: str) -> Dict[str, Any]:
"""模拟发送邮件"""
global MOCK_EMAILS_DB
MOCK_EMAILS_DB.append(
Email(
id=str(len(MOCK_EMAILS_DB) + 1),
subject=subject,
sender="me@example.com",
recipients=[recipient],
date=datetime.now().isoformat(),
body=body
)
)
return {
"success": True,
"message": "邮件发送成功"
}
def sniff_contacts_mock(self, query: str) -> Dict[str, Any]:
"""模拟智能嗅探联系人"""
import re
emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', query)
phones = re.findall(r'1[3-9]\d{9}', query)
contacts = []
for i, email in enumerate(emails):
contacts.append({
"name": f"联系人{i+1}",
"email": email,
"phone": phones[i] if i < len(phones) else ""
})
return {
"contacts": contacts,
"count": len(contacts),
"suggestion": "是否添加这些联系人?"
}
# ========== 公共方法(自动选择模式)==========
async def list_contacts(self, user_id: str = "default") -> List[Contact]:
"""获取联系人列表(自动选择数据库或模拟模式)"""
if self._use_db:
return await self.list_contacts_db(user_id)
return self.list_contacts_mock(user_id)
async def add_contact(self, user_id: str, contact: Contact) -> bool:
"""添加联系人(自动选择数据库或模拟模式)"""
if self._use_db:
return await self.add_contact_db(user_id, contact)
return self.save_contact_mock(user_id, contact)
async def list_emails(self, user_id: str = "default") -> List[Email]:
"""查询邮件列表(目前用模拟)"""
return self.list_emails_mock()
async def generate_email_draft(self, query: str) -> Dict[str, str]:
"""生成邮件草稿(目前用模拟)"""
return self.generate_email_draft_mock(query)
async def send_email(self, user_id: str, recipient: str, subject: str, body: str) -> bool: async def send_email(self, user_id: str, recipient: str, subject: str, body: str) -> bool:
"""发送邮件(目前用模拟)""" """发送邮件"""
result = self.send_email_mock(recipient, subject, body) await self._init_mcp()
return result.get("success", False) result = await mcp_manager.execute(
"contact", "send_email",
user_id=user_id, recipient=recipient, subject=subject, body=body
)
return result.success
async def sniff_contacts(self, query: str) -> List[Contact]: async def sniff_contacts(self, query: str) -> List[Contact]:
"""智能嗅探联系人(目前用模拟)""" """智能嗅探联系人"""
result = self.sniff_contacts_mock(query) await self._init_mcp()
contact_dicts = result.get("contacts", []) result = await mcp_manager.execute(
return [ "contact", "sniff_contacts", query=query
Contact(
id=str(i+1),
name=c.get("name", ""),
phone=c.get("phone", ""),
email=c.get("email", ""),
company="",
position="",
created_at=datetime.now().isoformat()
) )
for i, c in enumerate(contact_dicts) if result.success:
] return result.data
return []
# 保持向后兼容的旧方法
def list_contacts_mock(self, user_id: str = "default") -> List[Contact]:
"""模拟查询(保留用于向后兼容)"""
import asyncio
try:
return asyncio.run(self.list_contacts(user_id))
except Exception:
return []
# 全局例(模拟模式,保留向后兼容) # 全局例(保持向后兼容)
contact_api = ContactAPIClient() contact_api = ContactAPIClient()

View File

@@ -1,133 +1,62 @@
""" """
词典API调用工具 词典API调用工具使用MCP统一接口
Dictionary API Client
支持 async 和真实数据库缓存
""" """
from typing import Dict, Any, Optional from typing import Dict, Any, Optional
from dataclasses import dataclass from dataclasses import dataclass
from ...mcp.mcp_manager import mcp_manager
from ...mcp.adapters import DictionaryAdapter
@dataclass @dataclass
class DictionaryAPIClient: class DictionaryAPIClient:
""" """
词典API客户端 - 可扩展支持多种API和数据库缓存 词典API客户端 - 使用MCP统一接口
保持向后兼容内部使用MCP适配器
""" """
# 可以配置多个API # 保留配置字段用于向后兼容
youdao_api_key: Optional[str] = None youdao_api_key: Optional[str] = None
youdao_api_secret: Optional[str] = None youdao_api_secret: Optional[str] = None
# 数据库 Repository可选用于缓存单词查询
word_repository: Optional[Any] = None word_repository: Optional[Any] = None
def __post_init__(self): def __post_init__(self):
"""初始化后,如果有 repository 则支持 async""" """初始化后设置MCP"""
import asyncio
try:
asyncio.create_task(self._init_mcp())
except RuntimeError:
pass pass
async def query_word_db(self, user_id: str, word: str) -> Optional[Dict[str, Any]]: async def _init_mcp(self):
"""从数据库缓存查询单词""" """初始化MCP系统"""
if not self.word_repository: if not mcp_manager.get_adapter("dictionary"):
return None mcp_manager.register_adapter(
try: DictionaryAdapter(word_repo=self.word_repository)
entity = await self.word_repository.search_by_word(user_id, word)
if entity:
return {
"phonetic": entity.phonetic,
"part_of_speech": entity.part_of_speech,
"definitions": [entity.definition] if entity.definition else [],
"examples": [entity.examples] if entity.examples else []
}
except Exception as e:
print(f"从数据库查询单词失败:{e}")
return None
async def cache_word_db(self, user_id: str, word: str, data: Dict[str, Any]):
"""把单词查询结果缓存到数据库"""
if not self.word_repository:
return
try:
from ...db.models import WordEntity
entity = WordEntity(
user_id=user_id,
word=word,
phonetic=data.get("phonetic", ""),
part_of_speech=data.get("part_of_speech", ""),
definition=data.get("definitions", [""])[0] if data.get("definitions") else "",
examples=data.get("examples", [""])[0] if data.get("examples") else ""
) )
await self.word_repository.insert(entity) await mcp_manager.initialize()
except Exception as e:
print(f"缓存单词到数据库失败:{e}")
async def query_word_youdao(self, word: str) -> Optional[Dict[str, Any]]: async def query_word(
""" self,
调用有道词典API查询单词async 版本) user_id: str = "default",
注意需要配置有道API密钥才能使用 word: str = "",
文档https://ai.youdao.com/doc.s#guide use_cache: bool = True
""" ) -> Dict[str, Any]:
if not self.youdao_api_key or not self.youdao_api_secret: """查询单词(统一入口)"""
return None await self._init_mcp()
result = await mcp_manager.execute(
try: "dictionary", "query_word",
# TODO: 实现真实的有道API调用用 httpx 或 aiohttp user_id=user_id, word=word, use_cache=use_cache
# 这里是示例结构 )
return None if result.success:
return result.data
except Exception as e: return self.query_word_mock(word)
print(f"有道API调用失败{e}")
return None
async def translate_baidu(self, text: str, from_lang: str = "auto", to_lang: str = "zh") -> Optional[Dict[str, Any]]:
"""
调用百度翻译APIasync 版本)
注意需要配置百度API密钥才能使用
文档https://fanyi-api.baidu.com/doc/21
"""
# TODO: 实现真实的百度翻译API调用用 httpx 或 aiohttp
return None
def query_word_mock(self, word: str) -> Dict[str, Any]: def query_word_mock(self, word: str) -> Dict[str, Any]:
""" """模拟查询(保留用于向后兼容)"""
模拟词典API - 目前用于演示
"""
mock_db = {
"serendipity": {
"phonetic": "/ˌserənˈdipədē/",
"part_of_speech": "n.",
"definitions": ["意外发现珍奇事物的能力", "机缘凑巧"],
"examples": ["Finding that old photo was pure serendipity."]
},
"ephemeral": {
"phonetic": "ˈfem(ə)rəl/",
"part_of_speech": "adj.",
"definitions": ["短暂的,瞬息的"],
"examples": ["Fame in the digital age is often ephemeral."]
},
"ubiquitous": {
"phonetic": "/yo͞oˈbikwədəs/",
"part_of_speech": "adj.",
"definitions": ["无处不在的", "普遍存在的"],
"examples": ["Smartphones have become ubiquitous in modern life."]
},
"eloquent": {
"phonetic": "/ˈeləkwənt/",
"part_of_speech": "adj.",
"definitions": ["雄辩的,有说服力的"],
"examples": ["She gave an eloquent speech at the conference."]
},
"resilient": {
"phonetic": "/rəˈzilyənt/",
"part_of_speech": "adj.",
"definitions": ["有复原力的,能适应的"],
"examples": ["The community has proven to be resilient in the face of challenges."]
}
}
if word.lower() in mock_db:
return mock_db[word.lower()]
else:
return { return {
"word": word,
"phonetic": "", "phonetic": "",
"part_of_speech": "n.", "part_of_speech": "n.",
"definitions": [f"{word} 的释义1", f"{word} 的释义2"], "definitions": [f"{word} 的释义1", f"{word} 的释义2"],
@@ -135,58 +64,19 @@ class DictionaryAPIClient:
} }
def translate_mock(self, text: str, from_lang: str = "auto", to_lang: str = "zh") -> Dict[str, Any]: def translate_mock(self, text: str, from_lang: str = "auto", to_lang: str = "zh") -> Dict[str, Any]:
""" """模拟翻译(保留用于向后兼容)"""
模拟翻译API - 目前用于演示
"""
translations = {
"你好": "Hello",
"hello": "你好",
"人工智能": "Artificial Intelligence",
"artificial intelligence": "人工智能",
"ai": "人工智能",
"大模型": "Large Language Model",
"自然语言处理": "Natural Language Processing"
}
return { return {
"translated_text": translations.get(text.lower(), f"【翻译结果{text}"), "translated_text": f"【翻译】{text}",
"confidence": 0.95 "confidence": 0.95
} }
def extract_terms_mock(self, text: str) -> list: def extract_terms_mock(self, text: str) -> list:
""" """模拟术语提取(保留用于向后兼容)"""
模拟术语提取API
"""
return [ return [
{"term": "AI", "type": "技术术语", "definition": "人工智能", "confidence": 0.95}, {"term": "AI", "type": "技术术语", "definition": "人工智能", "confidence": 0.95},
{"term": "LLM", "type": "技术术语", "definition": "大语言模型", "confidence": 0.92}, {"term": "大模型", "type": "技术术语", "definition": "大语言模型", "confidence": 0.92}
{"term": "NLP", "type": "技术术语", "definition": "自然语言处理", "confidence": 0.88}
] ]
# ========== 统一入口(优先查缓存) ==========
async def query_word(self, user_id: str = "default", word: str = "", use_cache: bool = True) -> Dict[str, Any]:
"""
查询单词(统一入口,优先查数据库缓存)
"""
# 1. 先查数据库缓存
if use_cache:
cached = await self.query_word_db(user_id, word)
if cached:
return cached
# 2. 查第三方 API暂未实现 # 全局单例(保持向后兼容
api_result = await self.query_word_youdao(word)
if api_result:
if use_cache:
await self.cache_word_db(user_id, word, api_result)
return api_result
# 3. 用模拟数据(兜底)
mock_result = self.query_word_mock(word)
if use_cache:
await self.cache_word_db(user_id, word, mock_result)
return mock_result
# 单例实例(模拟模式,保持向后兼容)
dictionary_api = DictionaryAPIClient() dictionary_api = DictionaryAPIClient()

View File

@@ -1,72 +1,61 @@
""" """
资讯子图API调用工具 资讯子图API调用工具使用MCP统一接口
News Analysis API Client
支持 async 和真实数据库缓存
""" """
from typing import Dict, Any, Optional, List from typing import Dict, Any, Optional, List
import random import random
from datetime import datetime from datetime import datetime
from dataclasses import dataclass from dataclasses import dataclass
from ...mcp.mcp_manager import mcp_manager
from ...mcp.adapters import NewsAdapter
@dataclass @dataclass
class NewsAPIClient: class NewsAPIClient:
""" """
资讯API客户端 - 可扩展支持多种API和数据库缓存 资讯API客户端 - 使用MCP统一接口
保持向后兼容内部使用MCP适配器
""" """
# 可以配置多个API如 NewsAPI, 今日头条, 百度新闻等) # 保留配置字段用于向后兼容
newsapi_key: Optional[str] = None newsapi_key: Optional[str] = None
# 数据库 Repository可选用于缓存新闻
news_repository: Optional[Any] = None news_repository: Optional[Any] = None
async def query_news_db(self, user_id: str, keyword: str) -> Optional[List[Dict[str, Any]]]: def __post_init__(self):
"""从数据库缓存查询新闻""" """初始化后设置MCP"""
if not self.news_repository: import asyncio
return None
try: try:
entities = await self.news_repository.search_by_keywords(user_id, keyword) asyncio.create_task(self._init_mcp())
if entities: except RuntimeError:
return [ pass
{
"title": e.title,
"source": e.source,
"summary": e.content,
"keywords": e.keywords.split(",") if e.keywords else [],
"author": "",
"published_at": e.created_at
}
for e in entities
]
except Exception as e:
print(f"从数据库查询新闻失败:{e}")
return None
async def cache_news_db(self, user_id: str, news: Dict[str, Any]): async def _init_mcp(self):
"""把新闻缓存到数据库""" """初始化MCP系统"""
if not self.news_repository: if not mcp_manager.get_adapter("news"):
return mcp_manager.register_adapter(
try: NewsAdapter(news_repo=self.news_repository)
from ...db.models import NewsEntity
entity = NewsEntity(
user_id=user_id,
title=news.get("title", ""),
content=news.get("summary", ""),
url=news.get("url", ""),
source=news.get("source", ""),
keywords=",".join(news.get("keywords", []))
) )
await self.news_repository.insert(entity) await mcp_manager.initialize()
except Exception as e:
print(f"缓存新闻到数据库失败:{e}") async def query_news(
self,
user_id: str = "default",
query: str = "",
use_cache: bool = True
) -> List[Dict[str, Any]]:
"""查询新闻(统一入口)"""
await self._init_mcp()
result = await mcp_manager.execute(
"news", "query_news",
user_id=user_id, query=query, use_cache=use_cache
)
if result.success:
return result.data
return self.query_news_mock(query)
def query_news_mock(self, query: str) -> List[Dict[str, Any]]: def query_news_mock(self, query: str) -> List[Dict[str, Any]]:
""" """模拟查询(保留用于向后兼容)"""
模拟查询资讯 - 目前用于演示
"""
# 模拟资讯数据库
mock_news = [ mock_news = [
{ {
"title": "OpenAI发布GPT-5智能再升级", "title": "OpenAI发布GPT-5智能再升级",
@@ -83,74 +72,44 @@ class NewsAPIClient:
"keywords": ["医疗", "大模型", "应用"], "keywords": ["医疗", "大模型", "应用"],
"author": "Medical Team", "author": "Medical Team",
"published_at": datetime.now().isoformat() "published_at": datetime.now().isoformat()
},
{
"title": "2026年AI行业发展趋势报告",
"source": "Business Daily",
"summary": "最新行业报告显示AI行业将继续保持高速增长企业数字化转型加速...",
"keywords": ["趋势", "AI", "商业"],
"author": "Business Team",
"published_at": datetime.now().isoformat()
} }
] ]
# 根据查询词简单过滤
results = [] results = []
query_lower = query.lower() query_lower = query.lower()
for news in mock_news: for news in mock_news:
if (query_lower in news["title"].lower() or if (query_lower in news["title"].lower() or
query_lower in news["summary"].lower() or query_lower in news["summary"].lower() or
any(keyword.lower() in query_lower for keyword in news["keywords"])): any(keyword.lower() in query_lower for keyword in news["keywords"])):
results.append(news) results.append(news)
# 如果没有匹配到,返回前两条 return results if results else mock_news[:2]
if not results:
results = mock_news[:2]
return results
def analyze_url_mock(self, url: str) -> Dict[str, Any]: def analyze_url_mock(self, url: str) -> Dict[str, Any]:
""" """模拟URL分析保留用于向后兼容"""
模拟URL分析 - 目前用于演示
"""
return { return {
"title": f"分析结果:{url}", "title": f"分析结果:{url}",
"source": "URL Analyzer", "source": "URL Analyzer",
"summary": "已完成对该URL的内容分析包含文章摘要和情感倾向判断...", "summary": "已完成对该URL的内容分析包含文章摘要和情感倾向判断...",
"keywords": ["News", "Analysis", url.split("/")[-1] if url else "unknown"] "keywords": ["News", "Analysis"]
} }
def extract_keywords_mock(self, text: str) -> List[str]: def extract_keywords_mock(self, text: str) -> List[str]:
""" """模拟关键词提取(保留用于向后兼容)"""
模拟关键词提取 - 目前用于演示 keywords = ["AI", "大模型", "应用场景", "行业趋势", "创新", "技术"]
""" result = [k for k in keywords if k.lower() in text.lower()]
# 简单的关键词提取模拟 return result if result else keywords[:4]
common_keywords = ["AI", "大模型", "应用场景", "行业趋势", "创新", "技术"]
result = []
for keyword in common_keywords:
if keyword.lower() in text.lower():
result.append(keyword)
# 如果没找到,返回默认关键词
if not result:
result = ["AI", "大模型", "应用场景", "行业趋势"]
return result
def generate_report_mock(self, query: str) -> str: def generate_report_mock(self, query: str) -> str:
""" """模拟报告生成(保留用于向后兼容)"""
模拟报告生成 - 目前用于演示 return f"""═══════════════════════════════════════════
"""
report = f"""═══════════════════════════════════════════
📊 资讯分析报告 📊 资讯分析报告
═══════════════════════════════════════════ ═══════════════════════════════════════════
主题:{query} 主题:{query}
📋 摘要: 📋 摘要:
这是一份关于 {query} 的资讯分析综合报告,包含最新行业动态和趋势分析 这是关于 {query} 的资讯分析综合报告。
🔍 主要发现: 🔍 主要发现:
1. AI技术持续快速发展 1. AI技术持续快速发展
@@ -161,36 +120,10 @@ class NewsAPIClient:
- AI - AI
- 大模型 - 大模型
- 数字化转型 - 数字化转型
- 创新
═══════════════════════════════════════════ ═══════════════════════════════════════════
💡 建议:继续关注行业动态,把握发展机遇!
""" """
return report
# ========== 统一入口(优先查缓存) ==========
async def query_news(self, user_id: str = "default", query: str = "", use_cache: bool = True) -> List[Dict[str, Any]]:
"""查询新闻(统一入口,优先查数据库缓存)"""
# 1. 先查数据库缓存
if use_cache:
cached = await self.query_news_db(user_id, query)
if cached:
return cached
# 2. 查第三方 API暂未实现
# api_result = await self.query_news_api(query)
# if api_result:
# for news in api_result:
# await self.cache_news_db(user_id, news)
# return api_result
# 3. 用模拟数据(兜底)
mock_result = self.query_news_mock(query)
if use_cache:
for news in mock_result:
await self.cache_news_db(user_id, news)
return mock_result
# 单例实例(模拟模式,保持向后兼容) # 全局单例(保持向后兼容)
news_api = NewsAPIClient() news_api = NewsAPIClient()

View File

@@ -0,0 +1,179 @@
# MCP 集成系统
## 概述
这是一个统一的外部接口管理层,集成了 MCP (Model Context Protocol),同时支持数据库缓存和降级到模拟数据。
## 架构设计
```
┌─────────────────────────────────────────────────────────┐
│ 子图 (Subgraphs) │
│ contact_api │ dictionary_api │ news_api │
└─────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────┐
│ MCP Manager (统一入口) │
│ ┌─────────────────────────────────────────────────┐ │
│ │ Adapters (适配器层) │ │
│ │ ContactAdapter │ DictionaryAdapter │ NewsAdapter│ │
│ └─────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────┘
┌─────────────────┼─────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ MCP Client │ │ Database │ │ Mock Data │
│ (真实服务) │ │ (缓存层) │ │ (降级层) │
└──────────────┘ └──────────────┘ └──────────────┘
```
## 目录结构
```
backend/app/mcp/
├── __init__.py # 模块初始化
├── mcp_manager.py # MCP管理器统一入口
├── mcp_client.py # MCP客户端
├── base_adapter.py # 适配器基类
├── mcp_config.example.yaml # 配置示例
├── mcp_example.py # 使用示例
└── adapters/
├── __init__.py
├── contact_adapter.py # 通讯录适配器
├── dictionary_adapter.py# 词典适配器
└── news_adapter.py # 新闻适配器
```
## 快速开始
### 1. 基本使用(自动降级)
现有的子图API已经无缝迁移无需修改代码
```python
# 通讯录 - 和之前一样使用
from backend.app.subgraphs.contact.api_client import contact_api
contacts = await contact_api.list_contacts(user_id="default")
# 词典 - 和之前一样使用
from backend.app.subgraphs.dictionary.api_client import dictionary_api
word_data = await dictionary_api.query_word(word="ephemeral")
# 新闻 - 和之前一样使用
from backend.app.subgraphs.news_analysis.api_client import news_api
news_list = await news_api.query_news(query="AI")
```
### 2. 直接使用MCP管理器
```python
from backend.app.mcp import mcp_manager, ContactAdapter, DictionaryAdapter, NewsAdapter
# 注册适配器
mcp_manager.register_adapter(ContactAdapter())
mcp_manager.register_adapter(DictionaryAdapter())
mcp_manager.register_adapter(NewsAdapter())
# 初始化
await mcp_manager.initialize()
# 统一调用接口
result = await mcp_manager.execute(
"dictionary",
"query_word",
word="serendipity",
user_id="default"
)
print(f"来源: {result.source}") # mcp_dictionary / database / mock
print(f"数据: {result.data}")
```
### 3. 配置MCP服务器
复制配置示例:
```bash
cp backend/app/mcp/mcp_config.example.yaml backend/app/mcp/mcp_config.yaml
```
编辑 `mcp_config.yaml`启用需要的MCP服务器
```yaml
mcp_servers:
# Gmail 邮件服务
gmail:
type: stdio
command: npx
args:
- "-y"
- "@modelcontextprotocol/server-gmail"
enabled: true
# GitHub
github:
type: stdio
command: npx
args:
- "-y"
- "@modelcontextprotocol/server-github"
env:
GITHUB_PERSONAL_ACCESS_TOKEN: "ghp_your_token_here"
enabled: true
```
## 特性
### 1. 三层降级策略
- **MCP层**: 优先使用真实的MCP服务
- **数据库层**: 其次使用数据库缓存
- **模拟层**: 最后降级到模拟数据,确保系统始终可用
### 2. 统一接口
所有外部服务都通过 `mcp_manager.execute()` 统一调用,返回标准化的 `AdapterResult`
### 3. 向后兼容
保留了原有的 `api_client` 接口,现有代码无需修改即可使用新系统。
### 4. 可扩展
通过继承 `BaseAdapter` 可以轻松添加新的适配器。
## 创建自定义适配器
```python
from backend.app.mcp import BaseAdapter, AdapterResult
class MyAdapter(BaseAdapter):
name = "my_service"
description = "我的自定义服务"
async def execute(self, action: str, **kwargs) -> AdapterResult:
# 1. 尝试MCP
# 2. 尝试数据库
# 3. 降级到模拟
pass
# 注册
mcp_manager.register_adapter(MyAdapter())
```
## 可用的MCP服务器
- **@modelcontextprotocol/server-filesystem** - 文件系统访问
- **@modelcontextprotocol/server-github** - GitHub 集成
- **@modelcontextprotocol/server-gmail** - Gmail 邮件
- **@modelcontextprotocol/server-brave-search** - 网页搜索
- 更多社区服务器...
## 完整示例
参见 `backend/app/mcp/mcp_example.py` 获取完整的使用示例。

View File

@@ -0,0 +1,112 @@
#!/usr/bin/env python3
"""
简化版MCP测试 - 直接测试mcp模块
"""
import asyncio
import sys
from pathlib import Path
# 直接添加mcp模块路径
sys.path.insert(0, str(Path(__file__).parent / "backend" / "app"))
async def test_mcp_direct():
"""直接测试MCP模块"""
print("=" * 70)
print("🧪 直接测试 MCP 模块")
print("=" * 70)
# 直接导入mcp子模块
print("\n[1/4] 导入MCP核心模块...")
try:
from mcp.mcp_manager import MCPManager, mcp_manager
from mcp.adapters.base_adapter import BaseAdapter, AdapterResult
print("✅ 核心模块导入成功")
except Exception as e:
print(f"❌ 核心模块导入失败: {e}")
import traceback
traceback.print_exc()
return False
# 导入适配器
print("\n[2/4] 导入适配器...")
try:
from mcp.adapters.contact_adapter import ContactAdapter
from mcp.adapters.dictionary_adapter import DictionaryAdapter
from mcp.adapters.news_adapter import NewsAdapter
print("✅ 适配器导入成功")
except Exception as e:
print(f"❌ 适配器导入失败: {e}")
import traceback
traceback.print_exc()
return False
# 测试适配器
print("\n[3/4] 测试各个适配器...")
print("\n📖 测试 DictionaryAdapter...")
dict_adapter = DictionaryAdapter()
result = dict_adapter._fallback("query_word", word="ephemeral")
print(f" 来源: {result.source}")
print(f" 成功: {result.success}")
print(f" 单词: {result.data.get('word', '')}")
print(f" 释义: {result.data.get('definitions', [])}")
print("\n📰 测试 NewsAdapter...")
news_adapter = NewsAdapter()
result = news_adapter._fallback("query_news", query="AI")
print(f" 来源: {result.source}")
print(f" 成功: {result.success}")
print(f" 数量: {len(result.data) if result.data else 0}")
print("\n👥 测试 ContactAdapter...")
contact_adapter = ContactAdapter()
result = contact_adapter._fallback("list_contacts", user_id="test")
print(f" 来源: {result.source}")
print(f" 成功: {result.success}")
print(f" 数量: {len(result.data) if result.data else 0}")
# 测试MCP管理器
print("\n[4/4] 测试 MCP Manager...")
try:
mcp_manager.register_adapter(ContactAdapter())
mcp_manager.register_adapter(DictionaryAdapter())
mcp_manager.register_adapter(NewsAdapter())
await mcp_manager.initialize()
print(f"✅ 可用适配器: {mcp_manager.get_available_adapters()}")
print(f"✅ 可用工具: {mcp_manager.get_available_tools()}")
# 测试通过manager调用
print("\n测试通过Manager调用...")
result = await mcp_manager.execute(
"dictionary", "query_word", word="serendipity", user_id="test"
)
print(f" 成功: {result.success}")
print(f" 来源: {result.source}")
except Exception as e:
print(f"❌ MCP Manager 测试失败: {e}")
import traceback
traceback.print_exc()
print("\n" + "=" * 70)
print("🎉 直接测试完成!")
print("=" * 70)
print("\n✅ MCP集成系统架构已就绪:")
print(" ┌─────────────────────────────────────────────┐")
print(" │ MCP Manager (统一入口) │")
print(" ├─────────────────────────────────────────────┤")
print(" │ ContactAdapter │ DictionaryAdapter │ News │")
print(" ├─────────────────────────────────────────────┤")
print(" │ MCP Client -> Database -> Mock (降级) │")
print(" └─────────────────────────────────────────────┘")
print("\n📖 文档: docs/MCP_INTEGRATION.md")
print("⚙️ 配置: backend/app/mcp/mcp_config.example.yaml")
return True
if __name__ == "__main__":
asyncio.run(test_mcp_direct())