export interface AlphaAdvantageConfig {
apiKey: string;
cacheTTL?: Partial<typeof DEFAULT_CACHE_TTL>;
baseURL?: string;
}
/**
* Validate that a stock symbol is provided and looks valid
*/
function validateSymbol(symbol: unknown): asserts symbol is string {
if (typeof symbol !== "string" || symbol.trim() === "") {
throw new McpError(ErrorCode.InvalidParams, "A valid stock symbol is required");
}
// Basic symbol validation (letters, numbers, dots)
const symbolRegex = /^[A-Za-z0-9.]+$/;
if (!symbolRegex.test(symbol)) {
throw new McpError(ErrorCode.InvalidParams, `Invalid stock symbol: ${symbol}`);
}
}
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类型定义可以防止错误并提高可维护性：
强类型
// Start-up logging
console.error('[Setup] Initializing AlphaAdvantage MCP server...');
// API request logging
console.error(`[API] Getting stock overview for ${symbol}`);
// Error handling with context
console.error(`[Error] Tool execution failed: ${error.message}`);
// Cache operations
console.error(`[Cache] Using cached data for: ${cacheKey}`);
提供全面的 API 详细信息（端点、身份验证、数据结构）显著提高了 Cline 实现有效 MCP 服务器的能力。
Here's the API documentation for the service:
[Paste API documentation here]
复制
帮助 Cline 构建您的 MCP 服务器的最有效方法之一是在开始时分享官方 API 文档：
4.尽早提供 API 文档
准备就绪后，使用聊天底部的开关切换到 ACT MODE 开始实施。
讨论问题范围
审查 API 文档
规划身份验证方法
设计工具界面
Cline 将自动以计划模式启动，指导您完成规划过程：
3. 按照协议进行工作
I want to build an MCP server for the AlphaAdvantage financial API.
It should allow me to get real-time stock data, perform technical
analysis, and retrieve company financial information.
# MCP Server Development Protocol
⚠️ CRITICAL: DO NOT USE attempt_completion BEFORE TESTING ⚠️
## Step 1: Planning (PLAN MODE)
- What problem does this tool solve?
- What API/service will it use?
- What are the authentication requirements?
□ Standard API key
□ OAuth (requires separate setup script)
□ Other credentials
## Step 2: Implementation (ACT MODE)
1. Bootstrap
- For web services, JavaScript integration, or Node.js environments:
```bash
npx @modelcontextprotocol/create-server my-server
cd my-server
npm install
```
- For data science, ML workflows, or Python environments:
```bash
pip install mcp
# Or with uv (recommended)
uv add "mcp[cli]"
```
2. Core Implementation
- Use MCP SDK
- Implement comprehensive logging
- TypeScript (for web/JS projects):
```typescript
console.error('[Setup] Initializing server...');
console.error('[API] Request to endpoint:', endpoint);
console.error('[Error] Failed with:', error);
```
- Python (for data science/ML projects):
```python
import logging
logging.error('[Setup] Initializing server...')
logging.error(f'[API] Request to endpoint: {endpoint}')
logging.error(f'[Error] Failed with: {str(error)}')
```
- Add type definitions
- Handle errors with context
- Implement rate limiting if needed
3. Configuration
- Get credentials from user if needed
- Add to MCP settings:
- For TypeScript projects:
```json
{
"mcpServers": {
"my-server": {
"command": "node",
"args": ["path/to/build/index.js"],
"env": {
"API_KEY": "key"
},
"disabled": false,
"autoApprove": []
}
}
}
```
- For Python projects:
```bash
# Directly with command line
mcp install server.py -v API_KEY=key
# Or in settings.json
{
"mcpServers": {
"my-server": {
"command": "python",
"args": ["server.py"],
"env": {
"API_KEY": "key"
},
"disabled": false,
"autoApprove": []
}
}
}
```
## Step 3: Testing (BLOCKER ⛔️)
<thinking>
BEFORE using attempt_completion, I MUST verify:
□ Have I tested EVERY tool?
□ Have I confirmed success from the user for each test?
□ Have I documented the test results?
If ANY answer is "no", I MUST NOT use attempt_completion.
</thinking>
1. Test Each Tool (REQUIRED)
□ Test each tool with valid inputs
□ Verify output format is correct
⚠️ DO NOT PROCEED UNTIL ALL TOOLS TESTED
## Step 4: Completion
❗ STOP AND VERIFY:
□ Every tool has been tested with valid inputs
□ Output format is correct for each tool
Only after ALL tools have been tested can attempt_completion be used.
## Key Requirements
- ✓ Must use MCP SDK
- ✓ Must have comprehensive logging
- ✓ Must test each tool individually
- ✓ Must handle errors gracefully
- ⛔️ NEVER skip testing before completion
